{"id":"b56cf5d473365d3674b70e1b9f9079c195debfbd56148bdf5aa0bb463743ad8e","title":"Causal Time Series Modeling of Supraglacial Lake Evolution in Greenland under Distribution Shift","argument":"The authors of “Causal Time Series Modeling of Supraglacial Lake Evolution in Greenland under Distribution Shift” propose RIC-TSC, a model for classifying how supraglacial lakes evolve. They use satellite and weather data, along with Joint PCMCI+ (J-PCMCI+), to identify predictors and their time lags that are shared across regions or specific to individual basins. The authors argue that modeling these causal relationships could help predictions transfer when conditions differ from those in the training data, rather than relying only on correlations that may not hold across regions or seasons.\n\nOn a balanced benchmark of manually labeled lakes from two contrasting melt seasons, the authors report that their causal models achieve up to 12.59% higher accuracy than correlation-based baselines under out-of-distribution evaluation. This is a result on that benchmark, not evidence of performance in other settings. The study’s central idea is to use causal discovery both to select predictors and to make the resulting model more interpretable. The abstract does not establish how well the reported advantage holds beyond the benchmark.","topicIds":["intelligence-and-discovery"],"domain":"science","claimType":"attributed reading","limits":"The reported accuracy result is from a balanced benchmark of 1,000 manually labeled lakes from two contrasting melt seasons; the abstract does not establish performance beyond that evaluation. The available evidence is the abstract, which does not provide details of the evaluation protocol or results for individual regions or basins.","speaker":{"name":"Hossain, Emam, Ferdous, Muhammad Hasan, Dunmire, Devon, Subramanian, Aneesh, Gani, Md Osman","roleAtSource":"Article author"},"source":{"title":"Causal Time Series Modeling of Supraglacial Lake Evolution in Greenland under Distribution Shift","publisher":"arXiv cs.AI","format":"Article","url":"https://arxiv.org/abs/2510.15265","publishedAt":"2025-10-17","dateBasis":"Date basis not provided."},"evidence":[{"text":"The authors propose RIC-TSC, a causal time-series classification framework for studying supraglacial lake evolution in Greenland.","excerpt":"We propose RIC-TSC, a regionally-informed causal time-series classification framework","url":"https://arxiv.org/abs/2510.15265","relationship":"Source-stated"},{"text":"The framework uses Joint PCMCI+ to identify predictors that are specific to regions or invariant across them, including their time lags.","excerpt":"we leverage Joint PCMCI+ (J-PCMCI+) to identify region-specific and invariant predictors of supraglacial lake evolution in Greenland.","url":"https://arxiv.org/abs/2510.15265","relationship":"Source-stated"},{"text":"In the reported evaluation, causal models achieved up to 12.59% higher accuracy than correlation-based baselines.","excerpt":"causal models achieve up to 12.59% higher accuracy than correlation-based baselines under out-of-distribution evaluation.","url":"https://arxiv.org/abs/2510.15265","relationship":"Source-stated"},{"text":"The benchmark contained 1,000 manually labeled lakes from two contrasting melt seasons.","excerpt":"On a balanced benchmark of 1000 manually labeled lakes from two contrasting melt seasons (2018-2019)","url":"https://arxiv.org/abs/2510.15265","relationship":"Source-stated"}],"sourceMedia":{"status":"not_found","sourceUrl":"https://arxiv.org/abs/2510.15265","checkedAt":"2026-11-11T20:36:22.621Z","items":[],"note":"No suitable media was found by the supported page extraction."},"assumptions":[],"openQuestion":{"attribution":"Open question","text":"How well would the reported accuracy advantage hold when RIC-TSC is evaluated on additional melt seasons or basins beyond the benchmark?"},"whatWouldChangeView":{"attribution":"Change condition not recorded","text":""},"editorialComparisons":[],"live":{"title":"Causal Time Series Modeling of Supraglacial Lake Evolution in Greenland under Distribution Shift","summary":"The authors of “Causal Time Series Modeling of Supraglacial Lake Evolution in Greenland under Distribution Shift” propose RIC-TSC, a model for classifying how supraglacial lakes evolve. They use satellite and weather data, along with Joint PCMCI+ (J-PCMCI+), to identify predictors and their time lags that are shared across regions or specific to individual basins. The authors argue that modeling these causal relationships could help predictions transfer when conditions differ from those in the training data, rather than relying only on correlations that may not hold across regions or seasons.\n\nOn a balanced benchmark of manually labeled lakes from two contrasting melt seasons, the authors report that their causal models achieve up to 12.59% higher accuracy than correlation-based baselines under out-of-distribution evaluation. This is a result on that benchmark, not evidence of performance in other settings. The study’s central idea is to use causal discovery both to select predictors and to make the resulting model more interpretable. The abstract does not establish how well the reported advantage holds beyond the benchmark.","question":"How well would the reported accuracy advantage hold when RIC-TSC is evaluated on additional melt seasons or basins beyond the benchmark?","claims":[{"text":"The authors propose RIC-TSC, a causal time-series classification framework for studying supraglacial lake evolution in Greenland.","excerpt":"We propose RIC-TSC, a regionally-informed causal time-series classification framework","support":"source-stated"},{"text":"The framework uses Joint PCMCI+ to identify predictors that are specific to regions or invariant across them, including their time lags.","excerpt":"we leverage Joint PCMCI+ (J-PCMCI+) to identify region-specific and invariant predictors of supraglacial lake evolution in Greenland.","support":"source-stated"},{"text":"In the reported evaluation, causal models achieved up to 12.59% higher accuracy than correlation-based baselines.","excerpt":"causal models achieve up to 12.59% higher accuracy than correlation-based baselines under out-of-distribution evaluation.","support":"source-stated"},{"text":"The benchmark contained 1,000 manually labeled lakes from two contrasting melt seasons.","excerpt":"On a balanced benchmark of 1000 manually labeled lakes from two contrasting melt seasons (2018-2019)","support":"source-stated"}],"limitations":["The reported accuracy result is from a balanced benchmark of 1,000 manually labeled lakes from two contrasting melt seasons; the abstract does not establish performance beyond that evaluation.","The available evidence is the abstract, which does not provide details of the evaluation protocol or results for individual regions or basins."],"mediaId":"b56456460bc88e0db047f3ece04ceaf8ffe9a777e708429185daf0ccde37359e","correctionReason":null,"id":"b56cf5d473365d3674b70e1b9f9079c195debfbd56148bdf5aa0bb463743ad8e","publicationId":"36a151fe-9fa0-4a07-8029-fdece931183f","version":1,"sourceUrl":"https://arxiv.org/abs/2510.15265","sourceTitle":"Causal Time Series Modeling of Supraglacial Lake Evolution in Greenland under Distribution Shift","publisher":"arXiv cs.AI","publishedAt":null,"originalPublished":{"value":"2025-10-17","precision":"day","basis":"publisher_citation_date"},"firstObservedAt":"2026-11-11T05:09:22.732Z","createdAt":"2026-11-11T19:32:11.014Z","historical":true,"entityIds":["arxiv"],"topicIds":["intelligence-and-discovery"],"media":[{"id":"b56456460bc88e0db047f3ece04ceaf8ffe9a777e708429185daf0ccde37359e","kind":"article","url":"https://arxiv.org/abs/2510.15265","sourceUrl":"https://arxiv.org/abs/2510.15265","label":"Read original","provenance":"source_link","verification":{"status":"verified","checkedAt":"2026-11-11T19:20:34.339Z","method":"acquired_source","contentType":"text/html"},"recommendationReason":"Recommended by Jev for understanding this source; checked by Luna."}],"sourceMedia":{"status":"not_found","sourceUrl":"https://arxiv.org/abs/2510.15265","checkedAt":"2026-11-11T20:36:22.621Z","items":[],"note":"No suitable media was found by the supported page extraction."},"editorialDecision":{"outcome":"accept","reasonCodes":["material_development"],"rubricVersion":"stream-admission-v5","mediaId":"b56456460bc88e0db047f3ece04ceaf8ffe9a777e708429185daf0ccde37359e","confidence":0.68,"provider":"typesafe","model":"jev-1.13.0","inputHash":"579ef4069d93b6c77c150c4caaada13f4ab0a7c2ece4b8154d48d2885f9550c7","decidedAt":"2026-11-11T19:20:37.098Z"},"provenance":{"textHash":"611cf6b94fcece5e431cbbddcd5ced44ac8b2dd0a31417efe4d2273ad054b7c5","observationId":"bb34c8d468584c98d1a9747e9d8792c49145737a744d1d1198610349f3ca4c51","retrievedAt":"2026-11-11T19:20:33.963Z","kind":"publisher-page","preparer":{"model":"gpt-6-luna","runId":"0e685ecc-0ff2-4d97-87a3-e0512c2b33fd"},"reviewer":{"model":"gpt-6-luna","runId":"a5a6846d-bdac-43d3-82f9-638657e89303"}},"audit":{"status":"uncertain","reviewedAt":"2026-11-11T19:32:11.014Z","model":"anthropic/claude-opus-5.5"},"sourceAttribution":{"authors":[{"name":"Hossain, Emam","url":null,"kind":"unknown"},{"name":"Ferdous, Muhammad Hasan","url":null,"kind":"unknown"},{"name":"Dunmire, Devon","url":null,"kind":"unknown"},{"name":"Subramanian, Aneesh","url":null,"kind":"unknown"},{"name":"Gani, Md Osman","url":null,"kind":"unknown"}],"authorRole":"article-author","hosts":[],"status":"stated","authorRoster":{"truncated":false,"omitted":0,"assertionGroupsOmitted":0},"participation":[{"actor":{"name":"Hossain, Emam","url":null,"kind":"unknown","actorId":null},"role":"author","scope":{"kind":"work-credit","locator":null},"literalCredit":"Hossain, Emam","status":"stated","provenance":{"basis":"head-meta","sourceUrl":"https://arxiv.org/abs/2510.15265","locator":"head/meta[name=author|citation_author]"},"assertionId":"139523104fa3c504283a01fcb39a511c94d3f7251376284b97688c3fe95e50c3:participation:0","identity":{"version":"entity-identity-v1","status":"unresolved","actorId":null,"canonicalActorId":null,"candidateActorIds":[],"assertions":[],"sourceObservedAt":"2026-11-11T20:36:22.621Z","knowledgeAsOf":null},"sourceVersion":{"snapshotId":"139523104fa3c504283a01fcb39a511c94d3f7251376284b97688c3fe95e50c3","sourceUrl":"https://arxiv.org/abs/2510.15265","contentSha256":"be533b99d9ac300ec414fb9cd3a1d96fb77ca61ee64018b4bb4d9491ce10a60c","textHash":"611cf6b94fcece5e431cbbddcd5ced44ac8b2dd0a31417efe4d2273ad054b7c5","observedAt":"2026-11-11T20:36:22.621Z"}},{"actor":{"name":"Ferdous, Muhammad Hasan","url":null,"kind":"unknown","actorId":null},"role":"author","scope":{"kind":"work-credit","locator":null},"literalCredit":"Ferdous, Muhammad Hasan","status":"stated","provenance":{"basis":"head-meta","sourceUrl":"https://arxiv.org/abs/2510.15265","locator":"head/meta[name=author|citation_author]"},"assertionId":"139523104fa3c504283a01fcb39a511c94d3f7251376284b97688c3fe95e50c3:participation:1","identity":{"version":"entity-identity-v1","status":"unresolved","actorId":null,"canonicalActorId":null,"candidateActorIds":[],"assertions":[],"sourceObservedAt":"2026-11-11T20:36:22.621Z","knowledgeAsOf":null},"sourceVersion":{"snapshotId":"139523104fa3c504283a01fcb39a511c94d3f7251376284b97688c3fe95e50c3","sourceUrl":"https://arxiv.org/abs/2510.15265","contentSha256":"be533b99d9ac300ec414fb9cd3a1d96fb77ca61ee64018b4bb4d9491ce10a60c","textHash":"611cf6b94fcece5e431cbbddcd5ced44ac8b2dd0a31417efe4d2273ad054b7c5","observedAt":"2026-11-11T20:36:22.621Z"}},{"actor":{"name":"Dunmire, Devon","url":null,"kind":"unknown","actorId":null},"role":"author","scope":{"kind":"work-credit","locator":null},"literalCredit":"Dunmire, Devon","status":"stated","provenance":{"basis":"head-meta","sourceUrl":"https://arxiv.org/abs/2510.15265","locator":"head/meta[name=author|citation_author]"},"assertionId":"139523104fa3c504283a01fcb39a511c94d3f7251376284b97688c3fe95e50c3:participation:2","identity":{"version":"entity-identity-v1","status":"unresolved","actorId":null,"canonicalActorId":null,"candidateActorIds":[],"assertions":[],"sourceObservedAt":"2026-11-11T20:36:22.621Z","knowledgeAsOf":null},"sourceVersion":{"snapshotId":"139523104fa3c504283a01fcb39a511c94d3f7251376284b97688c3fe95e50c3","sourceUrl":"https://arxiv.org/abs/2510.15265","contentSha256":"be533b99d9ac300ec414fb9cd3a1d96fb77ca61ee64018b4bb4d9491ce10a60c","textHash":"611cf6b94fcece5e431cbbddcd5ced44ac8b2dd0a31417efe4d2273ad054b7c5","observedAt":"2026-11-11T20:36:22.621Z"}},{"actor":{"name":"Subramanian, Aneesh","url":null,"kind":"unknown","actorId":null},"role":"author","scope":{"kind":"work-credit","locator":null},"literalCredit":"Subramanian, Aneesh","status":"stated","provenance":{"basis":"head-meta","sourceUrl":"https://arxiv.org/abs/2510.15265","locator":"head/meta[name=author|citation_author]"},"assertionId":"139523104fa3c504283a01fcb39a511c94d3f7251376284b97688c3fe95e50c3:participation:3","identity":{"version":"entity-identity-v1","status":"unresolved","actorId":null,"canonicalActorId":null,"candidateActorIds":[],"assertions":[],"sourceObservedAt":"2026-11-11T20:36:22.621Z","knowledgeAsOf":null},"sourceVersion":{"snapshotId":"139523104fa3c504283a01fcb39a511c94d3f7251376284b97688c3fe95e50c3","sourceUrl":"https://arxiv.org/abs/2510.15265","contentSha256":"be533b99d9ac300ec414fb9cd3a1d96fb77ca61ee64018b4bb4d9491ce10a60c","textHash":"611cf6b94fcece5e431cbbddcd5ced44ac8b2dd0a31417efe4d2273ad054b7c5","observedAt":"2026-11-11T20:36:22.621Z"}},{"actor":{"name":"Gani, Md Osman","url":null,"kind":"unknown","actorId":null},"role":"author","scope":{"kind":"work-credit","locator":null},"literalCredit":"Gani, Md Osman","status":"stated","provenance":{"basis":"head-meta","sourceUrl":"https://arxiv.org/abs/2510.15265","locator":"head/meta[name=author|citation_author]"},"assertionId":"139523104fa3c504283a01fcb39a511c94d3f7251376284b97688c3fe95e50c3:participation:4","identity":{"version":"entity-identity-v1","status":"unresolved","actorId":null,"canonicalActorId":null,"candidateActorIds":[],"assertions":[],"sourceObservedAt":"2026-11-11T20:36:22.621Z","knowledgeAsOf":null},"sourceVersion":{"snapshotId":"139523104fa3c504283a01fcb39a511c94d3f7251376284b97688c3fe95e50c3","sourceUrl":"https://arxiv.org/abs/2510.15265","contentSha256":"be533b99d9ac300ec414fb9cd3a1d96fb77ca61ee64018b4bb4d9491ce10a60c","textHash":"611cf6b94fcece5e431cbbddcd5ced44ac8b2dd0a31417efe4d2273ad054b7c5","observedAt":"2026-11-11T20:36:22.621Z"}}],"participationCoverage":{"total":5,"returned":5,"complete":true,"fullAssertions":"source-metadata-endpoint"},"distribution":null,"publisher":null,"sourceUrl":"https://arxiv.org/abs/2510.15265","snapshotId":"139523104fa3c504283a01fcb39a511c94d3f7251376284b97688c3fe95e50c3","contentSha256":"be533b99d9ac300ec414fb9cd3a1d96fb77ca61ee64018b4bb4d9491ce10a60c","textHash":"611cf6b94fcece5e431cbbddcd5ced44ac8b2dd0a31417efe4d2273ad054b7c5","observedAt":"2026-11-11T20:36:22.621Z","basis":"publisher-page-metadata","sourceLinks":45,"linksTruncated":false,"metadataUrl":"/api/pipeline/stream/b56cf5d473365d3674b70e1b9f9079c195debfbd56148bdf5aa0bb463743ad8e/source"}},"canonicalUrl":"https://escapemeridian.com/readings/causal-time-series-modeling-of-supraglacial-lake-evolution-in-b56cf5d4","formats":{"html":"/readings/causal-time-series-modeling-of-supraglacial-lake-evolution-in-b56cf5d4","markdown":"/readings/causal-time-series-modeling-of-supraglacial-lake-evolution-in-b56cf5d4.md","json":"/readings/causal-time-series-modeling-of-supraglacial-lake-evolution-in-b56cf5d4.json"},"attribution":"Headline and summary by Escape Meridian, prepared by Luna from the attributed source. A source check is not independent confirmation of the source’s claims.","maintainedGuideLinks":[],"readerContext":{"version":"reader-context-v1","attribution":"Reference context selected by Escape Meridian; separate from source evidence. Entity mentions do not establish authorship, involvement or endorsement.","terms":[{"id":"term-time-series","name":"Time-series","explanation":"Observations arranged over time, such as monthly sales; forecasting uses their patterns to estimate later values.","referenceUrl":"https://developers.google.com/machine-learning/glossary#time-series-analysis"},{"id":"term-distribution-shift","name":"Distribution shift","explanation":"A change between the data a model was trained on and the data it meets in use, which can lower its accuracy.","referenceUrl":"https://en.wikipedia.org/wiki/Domain_adaptation"},{"id":"term-benchmark","name":"Benchmark","explanation":"A defined set of tests used to compare systems. Results depend on the tasks and measures selected.","referenceUrl":"https://arxiv.org/abs/2211.09110"}],"entities":[{"id":"arxiv","name":"arXiv","kind":"organization","context":"arXiv is a research manuscript repository where authors share papers that may not yet have been peer reviewed.","referenceUrls":["https://arxiv.org/","https://info.arxiv.org/help/api/index.html"],"path":"/entities/arxiv","json":"/entities/arxiv.json","markdown":"/entities/arxiv.md"},{"id":"time","name":"TIME","kind":"organization","context":"TIME is a news magazine publishing reporting on world affairs, business, technology and the workers behind digital services.","referenceUrls":["https://time.com/"],"path":"/entities/time","json":"/entities/time.json","markdown":"/entities/time.md"}]},"researchQuestions":[],"withdrawn":false,"references":{"schemaVersion":1,"target":{"type":"reading","id":"b56cf5d473365d3674b70e1b9f9079c195debfbd56148bdf5aa0bb463743ad8e","revision":"36a151fe-9fa0-4a07-8029-fdece931183f","revisionKind":"publication-id","title":"Causal Time Series Modeling of Supraglacial Lake Evolution in Greenland under Distribution Shift","url":"https://escapemeridian.com/readings/causal-time-series-modeling-of-supraglacial-lake-evolution-in-b56cf5d4"},"source":{"type":"source","id":"https://arxiv.org/abs/2510.15265","revision":"611cf6b94fcece5e431cbbddcd5ced44ac8b2dd0a31417efe4d2273ad054b7c5","revisionKind":"sha256-source-text","title":"Causal Time Series Modeling of Supraglacial Lake Evolution in Greenland under Distribution Shift","url":"https://arxiv.org/abs/2510.15265"},"status":"available","items":[],"next":null,"scope":"Explicit citations in public readings and public file attachments to this reading. Shared topics are not citations. Other artifact types need an explicit reference adapter."},"revisions":[{"id":"b56cf5d473365d3674b70e1b9f9079c195debfbd56148bdf5aa0bb463743ad8e","title":"Causal Time Series Modeling of Supraglacial Lake Evolution in Greenland under Distribution Shift","argument":"The authors of “Causal Time Series Modeling of Supraglacial Lake Evolution in Greenland under Distribution Shift” propose RIC-TSC, a model for classifying how supraglacial lakes evolve. They use satellite and weather data, along with Joint PCMCI+ (J-PCMCI+), to identify predictors and their time lags that are shared across regions or specific to individual basins. The authors argue that modeling these causal relationships could help predictions transfer when conditions differ from those in the training data, rather than relying only on correlations that may not hold across regions or seasons.\n\nOn a balanced benchmark of manually labeled lakes from two contrasting melt seasons, the authors report that their causal models achieve up to 12.59% higher accuracy than correlation-based baselines under out-of-distribution evaluation. This is a result on that benchmark, not evidence of performance in other settings. The study’s central idea is to use causal discovery both to select predictors and to make the resulting model more interpretable. The abstract does not establish how well the reported advantage holds beyond the benchmark.","topicIds":["intelligence-and-discovery"],"domain":"science","claimType":"attributed reading","limits":"The reported accuracy result is from a balanced benchmark of 1,000 manually labeled lakes from two contrasting melt seasons; the abstract does not establish performance beyond that evaluation. The available evidence is the abstract, which does not provide details of the evaluation protocol or results for individual regions or basins.","speaker":{"name":"Hossain, Emam, Ferdous, Muhammad Hasan, Dunmire, Devon, Subramanian, Aneesh, Gani, Md Osman","roleAtSource":"Article author"},"source":{"title":"Causal Time Series Modeling of Supraglacial Lake Evolution in Greenland under Distribution Shift","publisher":"arXiv cs.AI","format":"Article","url":"https://arxiv.org/abs/2510.15265","publishedAt":"2025-10-17","dateBasis":"Date basis not provided."},"evidence":[{"text":"The authors propose RIC-TSC, a causal time-series classification framework for studying supraglacial lake evolution in Greenland.","excerpt":"We propose RIC-TSC, a regionally-informed causal time-series classification framework","url":"https://arxiv.org/abs/2510.15265","relationship":"Source-stated"},{"text":"The framework uses Joint PCMCI+ to identify predictors that are specific to regions or invariant across them, including their time lags.","excerpt":"we leverage Joint PCMCI+ (J-PCMCI+) to identify region-specific and invariant predictors of supraglacial lake evolution in Greenland.","url":"https://arxiv.org/abs/2510.15265","relationship":"Source-stated"},{"text":"In the reported evaluation, causal models achieved up to 12.59% higher accuracy than correlation-based baselines.","excerpt":"causal models achieve up to 12.59% higher accuracy than correlation-based baselines under out-of-distribution evaluation.","url":"https://arxiv.org/abs/2510.15265","relationship":"Source-stated"},{"text":"The benchmark contained 1,000 manually labeled lakes from two contrasting melt seasons.","excerpt":"On a balanced benchmark of 1000 manually labeled lakes from two contrasting melt seasons (2018-2019)","url":"https://arxiv.org/abs/2510.15265","relationship":"Source-stated"}],"sourceMedia":{"status":"not_found","sourceUrl":"https://arxiv.org/abs/2510.15265","checkedAt":"2026-11-11T20:36:22.621Z","items":[],"note":"No suitable media was found by the supported page extraction."},"assumptions":[],"openQuestion":{"attribution":"Open question","text":"How well would the reported accuracy advantage hold when RIC-TSC is evaluated on additional melt seasons or basins beyond the benchmark?"},"whatWouldChangeView":{"attribution":"Change condition not recorded","text":""},"editorialComparisons":[],"live":{"title":"Causal Time Series Modeling of Supraglacial Lake Evolution in Greenland under Distribution Shift","summary":"The authors of “Causal Time Series Modeling of Supraglacial Lake Evolution in Greenland under Distribution Shift” propose RIC-TSC, a model for classifying how supraglacial lakes evolve. They use satellite and weather data, along with Joint PCMCI+ (J-PCMCI+), to identify predictors and their time lags that are shared across regions or specific to individual basins. The authors argue that modeling these causal relationships could help predictions transfer when conditions differ from those in the training data, rather than relying only on correlations that may not hold across regions or seasons.\n\nOn a balanced benchmark of manually labeled lakes from two contrasting melt seasons, the authors report that their causal models achieve up to 12.59% higher accuracy than correlation-based baselines under out-of-distribution evaluation. This is a result on that benchmark, not evidence of performance in other settings. The study’s central idea is to use causal discovery both to select predictors and to make the resulting model more interpretable. The abstract does not establish how well the reported advantage holds beyond the benchmark.","question":"How well would the reported accuracy advantage hold when RIC-TSC is evaluated on additional melt seasons or basins beyond the benchmark?","claims":[{"text":"The authors propose RIC-TSC, a causal time-series classification framework for studying supraglacial lake evolution in Greenland.","excerpt":"We propose RIC-TSC, a regionally-informed causal time-series classification framework","support":"source-stated"},{"text":"The framework uses Joint PCMCI+ to identify predictors that are specific to regions or invariant across them, including their time lags.","excerpt":"we leverage Joint PCMCI+ (J-PCMCI+) to identify region-specific and invariant predictors of supraglacial lake evolution in Greenland.","support":"source-stated"},{"text":"In the reported evaluation, causal models achieved up to 12.59% higher accuracy than correlation-based baselines.","excerpt":"causal models achieve up to 12.59% higher accuracy than correlation-based baselines under out-of-distribution evaluation.","support":"source-stated"},{"text":"The benchmark contained 1,000 manually labeled lakes from two contrasting melt seasons.","excerpt":"On a balanced benchmark of 1000 manually labeled lakes from two contrasting melt seasons (2018-2019)","support":"source-stated"}],"limitations":["The reported accuracy result is from a balanced benchmark of 1,000 manually labeled lakes from two contrasting melt seasons; the abstract does not establish performance beyond that evaluation.","The available evidence is the abstract, which does not provide details of the evaluation protocol or results for individual regions or basins."],"mediaId":"b56456460bc88e0db047f3ece04ceaf8ffe9a777e708429185daf0ccde37359e","correctionReason":null,"id":"b56cf5d473365d3674b70e1b9f9079c195debfbd56148bdf5aa0bb463743ad8e","publicationId":"36a151fe-9fa0-4a07-8029-fdece931183f","version":1,"sourceUrl":"https://arxiv.org/abs/2510.15265","sourceTitle":"Causal Time Series Modeling of Supraglacial Lake Evolution in Greenland under Distribution Shift","publisher":"arXiv cs.AI","publishedAt":null,"originalPublished":{"value":"2025-10-17","precision":"day","basis":"publisher_citation_date"},"firstObservedAt":"2026-11-11T05:09:22.732Z","createdAt":"2026-11-11T19:32:11.014Z","historical":true,"entityIds":["arxiv"],"topicIds":["intelligence-and-discovery"],"media":[{"id":"b56456460bc88e0db047f3ece04ceaf8ffe9a777e708429185daf0ccde37359e","kind":"article","url":"https://arxiv.org/abs/2510.15265","sourceUrl":"https://arxiv.org/abs/2510.15265","label":"Read original","provenance":"source_link","verification":{"status":"verified","checkedAt":"2026-11-11T19:20:34.339Z","method":"acquired_source","contentType":"text/html"},"recommendationReason":"Recommended by Jev for understanding this source; checked by Luna."}],"sourceMedia":{"status":"not_found","sourceUrl":"https://arxiv.org/abs/2510.15265","checkedAt":"2026-11-11T20:36:22.621Z","items":[],"note":"No suitable media was found by the supported page extraction."},"editorialDecision":{"outcome":"accept","reasonCodes":["material_development"],"rubricVersion":"stream-admission-v5","mediaId":"b56456460bc88e0db047f3ece04ceaf8ffe9a777e708429185daf0ccde37359e","confidence":0.68,"provider":"typesafe","model":"jev-1.13.0","inputHash":"579ef4069d93b6c77c150c4caaada13f4ab0a7c2ece4b8154d48d2885f9550c7","decidedAt":"2026-11-11T19:20:37.098Z"},"provenance":{"textHash":"611cf6b94fcece5e431cbbddcd5ced44ac8b2dd0a31417efe4d2273ad054b7c5","observationId":"bb34c8d468584c98d1a9747e9d8792c49145737a744d1d1198610349f3ca4c51","retrievedAt":"2026-11-11T19:20:33.963Z","kind":"publisher-page","preparer":{"model":"gpt-6-luna","runId":"0e685ecc-0ff2-4d97-87a3-e0512c2b33fd"},"reviewer":{"model":"gpt-6-luna","runId":"a5a6846d-bdac-43d3-82f9-638657e89303"}},"audit":{"status":"uncertain","reviewedAt":"2026-11-11T19:32:11.014Z","model":"anthropic/claude-opus-5.5"},"sourceAttribution":{"authors":[{"name":"Hossain, Emam","url":null,"kind":"unknown"},{"name":"Ferdous, Muhammad Hasan","url":null,"kind":"unknown"},{"name":"Dunmire, Devon","url":null,"kind":"unknown"},{"name":"Subramanian, Aneesh","url":null,"kind":"unknown"},{"name":"Gani, Md Osman","url":null,"kind":"unknown"}],"authorRole":"article-author","hosts":[],"status":"stated","authorRoster":{"truncated":false,"omitted":0,"assertionGroupsOmitted":0},"participation":[{"actor":{"name":"Hossain, Emam","url":null,"kind":"unknown","actorId":null},"role":"author","scope":{"kind":"work-credit","locator":null},"literalCredit":"Hossain, Emam","status":"stated","provenance":{"basis":"head-meta","sourceUrl":"https://arxiv.org/abs/2510.15265","locator":"head/meta[name=author|citation_author]"},"assertionId":"139523104fa3c504283a01fcb39a511c94d3f7251376284b97688c3fe95e50c3:participation:0","identity":{"version":"entity-identity-v1","status":"unresolved","actorId":null,"canonicalActorId":null,"candidateActorIds":[],"assertions":[],"sourceObservedAt":"2026-11-11T20:36:22.621Z","knowledgeAsOf":null},"sourceVersion":{"snapshotId":"139523104fa3c504283a01fcb39a511c94d3f7251376284b97688c3fe95e50c3","sourceUrl":"https://arxiv.org/abs/2510.15265","contentSha256":"be533b99d9ac300ec414fb9cd3a1d96fb77ca61ee64018b4bb4d9491ce10a60c","textHash":"611cf6b94fcece5e431cbbddcd5ced44ac8b2dd0a31417efe4d2273ad054b7c5","observedAt":"2026-11-11T20:36:22.621Z"}},{"actor":{"name":"Ferdous, Muhammad Hasan","url":null,"kind":"unknown","actorId":null},"role":"author","scope":{"kind":"work-credit","locator":null},"literalCredit":"Ferdous, Muhammad Hasan","status":"stated","provenance":{"basis":"head-meta","sourceUrl":"https://arxiv.org/abs/2510.15265","locator":"head/meta[name=author|citation_author]"},"assertionId":"139523104fa3c504283a01fcb39a511c94d3f7251376284b97688c3fe95e50c3:participation:1","identity":{"version":"entity-identity-v1","status":"unresolved","actorId":null,"canonicalActorId":null,"candidateActorIds":[],"assertions":[],"sourceObservedAt":"2026-11-11T20:36:22.621Z","knowledgeAsOf":null},"sourceVersion":{"snapshotId":"139523104fa3c504283a01fcb39a511c94d3f7251376284b97688c3fe95e50c3","sourceUrl":"https://arxiv.org/abs/2510.15265","contentSha256":"be533b99d9ac300ec414fb9cd3a1d96fb77ca61ee64018b4bb4d9491ce10a60c","textHash":"611cf6b94fcece5e431cbbddcd5ced44ac8b2dd0a31417efe4d2273ad054b7c5","observedAt":"2026-11-11T20:36:22.621Z"}},{"actor":{"name":"Dunmire, Devon","url":null,"kind":"unknown","actorId":null},"role":"author","scope":{"kind":"work-credit","locator":null},"literalCredit":"Dunmire, Devon","status":"stated","provenance":{"basis":"head-meta","sourceUrl":"https://arxiv.org/abs/2510.15265","locator":"head/meta[name=author|citation_author]"},"assertionId":"139523104fa3c504283a01fcb39a511c94d3f7251376284b97688c3fe95e50c3:participation:2","identity":{"version":"entity-identity-v1","status":"unresolved","actorId":null,"canonicalActorId":null,"candidateActorIds":[],"assertions":[],"sourceObservedAt":"2026-11-11T20:36:22.621Z","knowledgeAsOf":null},"sourceVersion":{"snapshotId":"139523104fa3c504283a01fcb39a511c94d3f7251376284b97688c3fe95e50c3","sourceUrl":"https://arxiv.org/abs/2510.15265","contentSha256":"be533b99d9ac300ec414fb9cd3a1d96fb77ca61ee64018b4bb4d9491ce10a60c","textHash":"611cf6b94fcece5e431cbbddcd5ced44ac8b2dd0a31417efe4d2273ad054b7c5","observedAt":"2026-11-11T20:36:22.621Z"}},{"actor":{"name":"Subramanian, Aneesh","url":null,"kind":"unknown","actorId":null},"role":"author","scope":{"kind":"work-credit","locator":null},"literalCredit":"Subramanian, Aneesh","status":"stated","provenance":{"basis":"head-meta","sourceUrl":"https://arxiv.org/abs/2510.15265","locator":"head/meta[name=author|citation_author]"},"assertionId":"139523104fa3c504283a01fcb39a511c94d3f7251376284b97688c3fe95e50c3:participation:3","identity":{"version":"entity-identity-v1","status":"unresolved","actorId":null,"canonicalActorId":null,"candidateActorIds":[],"assertions":[],"sourceObservedAt":"2026-11-11T20:36:22.621Z","knowledgeAsOf":null},"sourceVersion":{"snapshotId":"139523104fa3c504283a01fcb39a511c94d3f7251376284b97688c3fe95e50c3","sourceUrl":"https://arxiv.org/abs/2510.15265","contentSha256":"be533b99d9ac300ec414fb9cd3a1d96fb77ca61ee64018b4bb4d9491ce10a60c","textHash":"611cf6b94fcece5e431cbbddcd5ced44ac8b2dd0a31417efe4d2273ad054b7c5","observedAt":"2026-11-11T20:36:22.621Z"}},{"actor":{"name":"Gani, Md Osman","url":null,"kind":"unknown","actorId":null},"role":"author","scope":{"kind":"work-credit","locator":null},"literalCredit":"Gani, Md Osman","status":"stated","provenance":{"basis":"head-meta","sourceUrl":"https://arxiv.org/abs/2510.15265","locator":"head/meta[name=author|citation_author]"},"assertionId":"139523104fa3c504283a01fcb39a511c94d3f7251376284b97688c3fe95e50c3:participation:4","identity":{"version":"entity-identity-v1","status":"unresolved","actorId":null,"canonicalActorId":null,"candidateActorIds":[],"assertions":[],"sourceObservedAt":"2026-11-11T20:36:22.621Z","knowledgeAsOf":null},"sourceVersion":{"snapshotId":"139523104fa3c504283a01fcb39a511c94d3f7251376284b97688c3fe95e50c3","sourceUrl":"https://arxiv.org/abs/2510.15265","contentSha256":"be533b99d9ac300ec414fb9cd3a1d96fb77ca61ee64018b4bb4d9491ce10a60c","textHash":"611cf6b94fcece5e431cbbddcd5ced44ac8b2dd0a31417efe4d2273ad054b7c5","observedAt":"2026-11-11T20:36:22.621Z"}}],"participationCoverage":{"total":5,"returned":5,"complete":true,"fullAssertions":"source-metadata-endpoint"},"distribution":null,"publisher":null,"sourceUrl":"https://arxiv.org/abs/2510.15265","snapshotId":"139523104fa3c504283a01fcb39a511c94d3f7251376284b97688c3fe95e50c3","contentSha256":"be533b99d9ac300ec414fb9cd3a1d96fb77ca61ee64018b4bb4d9491ce10a60c","textHash":"611cf6b94fcece5e431cbbddcd5ced44ac8b2dd0a31417efe4d2273ad054b7c5","observedAt":"2026-11-11T20:36:22.621Z","basis":"publisher-page-metadata","sourceLinks":45,"linksTruncated":false,"metadataUrl":"/api/pipeline/stream/b56cf5d473365d3674b70e1b9f9079c195debfbd56148bdf5aa0bb463743ad8e/source"}}}],"audits":[{"publicationId":"36a151fe-9fa0-4a07-8029-fdece931183f","verdict":"uncertain","findings":[{"dimension":"attribution","status":"pass","explanation":"The reading attributes the proposal, method and accuracy result to the paper's authors and keeps the result framed as reported. It does not present the result as established fact or as Escape Meridian's view.","excerpt":"Authors:Emam Hossain, Muhammad Hasan Ferdous, Devon Dunmire, Aneesh Subramanian, Md Osman Gani"},{"dimension":"summary","status":"uncertain","explanation":"The reading is faithful but not readable on its own for a non-specialist. The central term 'supraglacial lakes' is never explained. 'Joint PCMCI+', 'out-of-distribution evaluation' and 'distribution shift' also appear without plain explanation. Smallest repair: keep these terms exactly, add term-library tooltips, and briefly say these are lakes forming on Greenland's ice surface. The reading also softens the authors' closing thesis that causal discovery is a pathway to generalizable, mechanistically grounded models. Restoring that attributed claim would preserve its force.","excerpt":"causal discovery is not only a means of feature selection but also a pathway to generalizable and mechanistically grounded models of dynamic Earth surface processes"},{"dimension":"date","status":"pass","explanation":"The originalPublished value of 2025-10-17 matches the arXiv v1 submission date. The 2026 feed date was correctly not used.","excerpt":"[Submitted on 17 Oct 2025]"},{"dimension":"support","status":"pass","explanation":"Each claim is stated in the abstract: the RIC-TSC proposal, the use of J-PCMCI+ for region-specific and invariant predictors with lags, the up to 12.59% gain under out-of-distribution evaluation, and the 1000-lake, two-season benchmark. The limitations correctly avoid extending the benchmark result to real-world reliability. The question about additional seasons or basins follows from the stated scope and is not leading.","excerpt":"causal models achieve up to 12.59% higher accuracy than correlation-based baselines under out-of-distribution evaluation"},{"dimension":"media","status":"pass","explanation":"The selected media is the verified direct link to the arXiv abstract page. That page is the actual source, and no better source media was found.","excerpt":null}],"createdAt":"2026-11-11T19:32:11.014Z","model":"anthropic/claude-opus-5.5"}],"correctionUrl":"https://escapemeridian.com/corrections/"}