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Record W1972037822 · doi:10.1029/2005eo400003

Arctic ocean study: Synthesis of model results and observations

2005· article· en· W1972037822 on OpenAlexaff
Andrey Proshutinsky, Jiayan Yang, Richard Krishfield, Rüdiger Gerdes, Michael Kärcher, Frank Kauker, C. Koeberle, Sirpa Häkkinen, W. D. Hibler, David M. Holland, M. Á. Morales Maqueda, Greg Holloway, Elizabeth Hunke, Wieslaw Maslowski, Michael Steele, J. Zhang

Bibliographic record

VenueEos · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicMethane Hydrates and Related Phenomena
Canadian institutionsNorth Pacific Marine Science OrganizationFisheries and Oceans Canada
FundersDivision of Materials ResearchWoods Hole Oceanographic Institution
KeywordsArcticContext (archaeology)ClimatologyOceanographyThe arcticEnvironmental scienceGeneral Circulation ModelCoupled model intercomparison projectClimate changeSea iceClimate modelOcean currentGeographyGeology

Abstract

fetched live from OpenAlex

Model development and simulations represent a comprehensive synthesis of observations with advances in numerous disciplines (physics; mathematics; and atmospheric, oceanic, cryospheric, and related sciences), enabling hypothesis testing via numerical experiments. For the Arctic Ocean, modeling has become one of the major instruments for understanding past conditions and explaining recently observed changes. In this context, the international Arctic Ocean Model Intercomparison Project (AOMiphttp://fish.cims.nyu.edu/project_aomip/overview. html) has investigated various aspects of ocean and sea ice changes for the time period 1948 to present. Among the major AOMIP themes are investigations of the origin and variability of Atlantic water (AW) circulation, mechanisms of accumulation and release of fresh water (FW), causes of sea level rise, and the role of tides in shaping climate.

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)0.003
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: Review · Consensus signal: none
Teacher disagreement score0.087
Threshold uncertainty score0.173

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.005
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.031
GPT teacher head0.237
Teacher spread0.207 · 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
GenreReview

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

Citations60
Published2005
Admission routes1
Has abstractyes

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