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Record W2559944463 · doi:10.2172/1233439

Final Report. Coupled simulations of Antarctic Ice-sheet/ocean interactions using POP and CISM

2015· report· en· W2559944463 on OpenAlexfundno aff
Xylar Asay‐Davis

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsnot available
FundersLos Alamos National LaboratoryLawrence Berkeley National LaboratoryUniversity of BristolYork UniversityStrongU.S. Department of Energy
KeywordsAntarctic ice sheetIce sheetClimatologyForcing (mathematics)CLARIONNational laboratoryIce-sheet modelMeteorologyOceanographySea iceGeologyCryosphereGeographyComputer scienceIce shelfEngineeringEngineering physics

Abstract

fetched live from OpenAlex

The project performed under this award, referred to from here on as CLARION (CoupLed simulations of Antarctic Ice-sheet/Ocean iNteractions), included important advances in two models of ice sheet and ocean interactions. Despite its short duration (one year), the project made significant progress on its three major foci. First, together with collaborator Daniel Martin at Lawrence Berkeley National Laboratory (LBNL), I developed the POPSICLES coupled ice sheet-ocean model to the point where it could perform a number of pan-Antarctic simulations under various forcing conditions. The results were presented at a number of major conferences and workshops worldwide, and are currently being incorporated into two manuscripts in preparation.

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)0.003
metaresearch head score (Gemma)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.026
Threshold uncertainty score0.088

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0260.008

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 head0.150
GPT teacher head0.367
Teacher spread0.217 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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