MétaCan
Menu
Back to cohort
Record W2084131940 · doi:10.1029/2005gl023047

Simulation of the last glacial inception with the green McGill Paleoclimate Model

2005· article· en· W2084131940 on OpenAlexaffabout
Zhaomin Wang, Anne‐Sophie B. Cochelin, Lawrence A. Mysak, Yi Wang

Bibliographic record

VenueGeophysical Research Letters · 2005
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsMcGill University
Fundersnot available
KeywordsPaleoclimatologyGeologyIce sheetGlacial periodClimatologyMilankovitch cyclesIce agePhysical geographyPaleontologyOceanographyClimate changeGeography

Abstract

fetched live from OpenAlex

The “green” McGill Paleoclimate Model (MPM), which includes an interactive vegetation component, is run between 122 and 80 kyr Before Present (BP) under Milankovitch forcing and Vostok‐derived atmospheric CO2 concentration. The model simulates the last glacial inception (LGI) at around 119 kyr BP, and the subsequent buildup of huge ice sheets over the high northern latitudes, especially North America. Due to the addition of a vegetation component and an improved land surface scheme in the MPM, the resulting ice sheet volume is relatively small over Eurasia but quite large over North America, which is in qualitative agreement with observations and represents a significant improvement over the LGI results from the previous version of the MPM. The reduction of the forest area at high northern latitudes during the inception phase, which is induced by decreased warm season insolation, is necessary for the ice sheets to grow over Eurasia and to have large ice sheet growth over North America.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.385
Threshold uncertainty score0.765

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0020.001
Research integrity0.0010.001
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 head0.038
GPT teacher head0.293
Teacher spread0.255 · 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 designSimulation or modeling
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

Citations29
Published2005
Admission routes2
Has abstractyes

Explore more

Same venueGeophysical Research LettersSame topicGeology and Paleoclimatology ResearchFrench-language works237,207