MétaCan
Menu
Back to cohort

Sea ice sensitivity to the parameterisation of open water area

2010· article· en· W2565919084 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Operational Oceanography · 2010
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsBedford Institute of Oceanography
FundersDivision of Ocean SciencesCanadian Foundation for Climate and Atmospheric Sciences
KeywordsSea iceIce waterVolume (thermodynamics)Sensitivity (control systems)Sea ice thicknessGeologySea ice growth processesCalibrationClimatologyEnvironmental scienceArctic ice packMathematicsThermodynamicsPhysics

Abstract

fetched live from OpenAlex

Based on version 2 of the Louvain-la-Neuve sea Ice Model (LIM2), sensitivity experiments reveal simple relations between ice conditions and the characteristic thickness parameter ho that appears in the parameterisation used to determine changes in open water area during ice growth. In particular, when ho is increased, the ice concentration is decreased during ice growth and increased during the subsequent melting season; the annual mean sea ice volume, thickness and extent all increase with ho. Calibration of ho makes it possible to adjust the model-simulated ice volume and thickness variations to be consistent with observations.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.014
Threshold uncertainty score0.609

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.015
GPT teacher head0.237
Teacher spread0.222 · 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