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Record W2768046970 · doi:10.1126/science.aan3001

Cordilleran Ice Sheet mass loss preceded climate reversals near the Pleistocene Termination

2017· article· en· W2768046970 on OpenAlexafffundabout
Brian Menounos, Brent M. Goehring, Gerald Osborn, Martin Margold, Brent Ward, Jeffrey D. Bond, Garry K. C. Clarke, John J. Clague, Thomas R. Lakeman, Johannes Koch, Marc W. Caffee, John Gosse, Arjen P. Stroeven, Julien Seguinot, Jakob Heyman

Bibliographic record

VenueScience · 2017
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsDalhousie UniversityKwantlen Polytechnic UniversityUniversity of British ColumbiaYukon UniversitySimon Fraser UniversityUniversity of CalgaryUniversity of Northern British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsIce sheetDeglaciationGeologyCryosphereIce-sheet modelGlacier morphologyPleistocenePaleontologyPhysical geographyGlacierIce tongueIce streamOceanographyClimatologyGlacial periodGeographySea ice

Abstract

fetched live from OpenAlex

The Cordilleran Ice Sheet (CIS) once covered an area comparable to that of Greenland. Previous geologic evidence and numerical models indicate that the ice sheet covered much of westernmost Canada as late as 12.5 thousand years ago (ka). New data indicate that substantial areas throughout westernmost Canada were ice free prior to 12.5 ka and some as early as 14.0 ka, with implications for climate dynamics and the timing of meltwater discharge to the Pacific and Arctic oceans. Early Bølling-Allerød warmth halved the mass of the CIS in as little as 500 years, causing 2.5 to 3.0 meters of sea-level rise. Dozens of cirque and valley glaciers, along with the southern margin of the CIS, advanced into recently deglaciated regions during the Bølling-Allerød and Younger Dryas.

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 score0.380
Threshold uncertainty score0.756

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.025
GPT teacher head0.287
Teacher spread0.263 · 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

Citations112
Published2017
Admission routes3
Has abstractyes

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