MétaCan
Menu
← Back to cohort
Record W4366606084 · doi:10.1002/9781119828242.ch2

Ice Physics and Physical Processes

2023· other· en· W4366606084 on OpenAlexaff
Mohammed Shokr, Nirmal K. Sinha

Bibliographic record

Venuenot available
Typeother
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsNational Research Council CanadaEnvironment and Climate Change Canada
Fundersnot available
KeywordsSea icePancake iceSea ice growth processesClear iceIce divideAntarctic sea iceGeologyFast iceArctic ice packDrift iceIcebergCryosphereMelt pondOceanographySea ice thickness

Abstract

fetched live from OpenAlex

This chapter starts with relevant information about water (freshwater and seawater), which affect the ice formation and the phase diagram of sea ice. It then addresses the subject of initial ice formation and the lateral and vertical ice growth and also presents thermodynamic ice growth models. Within the vertical growth part, the processes of entrapment of inclusions (salts and air) within the sea ice and the continuous desalination (brine drainage) are covered. Related to salt entrapment in sea ice, the chapter presents the process of compositional supercooling and covers the important features of the dendritic sea ice-water interface (which actually discriminate between sea ice and freshwater ice). It then focuses on ice deformation, ice decay and aging. The chapter finally addresses ice classes and covers a few commonly known ice regimes, namely polynyas, pancake ice, marginal ice zone, ice edge, and ice of land origin (i.e., icebergs and ice islands).

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.015
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0150.003

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 head0.011
GPT teacher head0.213
Teacher spread0.203 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2023
Admission routes1
Has abstractyes

Explore more

Same topicArctic and Antarctic ice dynamics→French-language works237,207→