MétaCan
Menu
Back to cohort
Record W2246483460

Multi-Year Ice Thickness: Knowns and Unknowns

2009· article· en· W2246483460 on OpenAlexfundvenueaboutno aff
Michelle Johnston, Daniel Masterson, Brian D. Wright

Bibliographic record

VenueNPARC · 2009
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsnot available
FundersTransport Canada
KeywordsBeaufort seaGeologyRidgeArcticArctic ice packSea iceThe arcticSverdrupClimatologyGeodesyOceanographyPaleontology
DOInot available

Abstract

fetched live from OpenAlex

Nearly 5000 direct measurements of multi-year ice thickness, compiled from studies spanning a period of 51 years, are used to identify some of the “knowns and unknowns” surrounding multiyear ice. Many of these studies reside in the grey literature, which makes this paper one the few in the open literature to include data from these not-often-seen reports. Individual thickness measurements on multi-year ice suggest that floes from the Beaufort, Central Canadian Arctic, High Arctic and Sverdrup Basin are of comparable thickness. The thickest multi-year ice, 40.2 m, was measured on a pressure ridge in the Canadian Beaufort. On average, the mean thickness is 5.6 m (±2.2 m) for a relatively level multi-year floe and 9.9 m (±4.7 m) for a pressure ridge. Floes with a mean thicknesses of 11.3 m, and pressure ridges with a mean thickness of 24.7 m have been measured, however.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.279
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0020.000

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 head0.023
GPT teacher head0.229
Teacher spread0.206 · 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 teacher head, not a consensus.

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

Citations12
Published2009
Admission routes3
Has abstractyes

Explore more

Same venueNPARCSame topicCryospheric studies and observationsFrench-language works237,207