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Record W4362720773 · doi:10.1029/2022gl101940

Flexural Response to Erosional Unloading of Continental Margins: An Example From the Bering Sea, USA

2023· article· en· W4362720773 on OpenAlexaff
Matthew A. Malkowski, Aaron T. Steelquist, G. E. Hilley

Bibliographic record

VenueGeophysical Research Letters · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsGeologyCanyonPleistoceneContinental marginPaleontologyErosionSubmarine canyonContinental shelfPassive marginQuaternaryUnconformityGeomorphologyEarly PleistoceneSea levelMargin (machine learning)OceanographyTectonicsRift

Abstract

fetched live from OpenAlex

Abstract The geodynamic response of continental margins to erosion may reveal current and past changes in the location of the continental slope. We model the three‐dimensional isostatic response to erosion along the retreating Beringian Margin to test the hypothesis that the margin and its canyons were dominantly eroded during the Pleistocene. Our results predict 900 m of flexural uplift, though evidence for this magnitude of uplift is not observed in Pleistocene and younger deposits, suggesting a substantial amount of margin erosion occurred pre‐Pleistocene. Uplift of this magnitude may be represented by a Late Miocene unconformity across the Bering Shelf and upwarped subsurface units at the base of the Beringian Margin. The distribution of uplift from varying canyon incision and margin retreat scenarios has implications for the extent of geodynamic response during erosional periods.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.172
Threshold uncertainty score0.342

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.092
GPT teacher head0.327
Teacher spread0.235 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2023
Admission routes1
Has abstractyes

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