MétaCan
Menu
Back to cohort
Record W6968943949 · doi:10.5443/11802

Thickness, Salinity, Temperature and Strength of Multi-Year Sea Ice, Beaufort Sea

2016· dataset· en· W6968943949 on OpenAlexaboutno aff

Bibliographic record

VenueCanadian Polar Data Network · 2016
Typedataset
Languageen
FieldAgricultural and Biological Sciences
TopicLand Rights and Reforms
Canadian institutionsnot available
Fundersnot available
KeywordsSea iceBoreholeSea ice thicknessArctic ice packSubmarine pipelineDrift iceAntarctic sea iceKeel

Abstract

fetched live from OpenAlex

The viability of newly developed equipment to measure the strength of multi-year ice at depths where no information presently exists was demonstrated during the first field program in May 2012 in Resolute, Nunavut. It was tested on hummocked multi-year ice from 3 to 20 May. Measurements were constrained to one hummocked multi-year ice floe for the purposes of testing the equipment. Ice cores were extracted from two boreholes to document the temperature and salinity of the ice to a maximum depth of 12 m. In situ strength tests were conducted in both boreholes at depth intervals of 30 cm to document changes in strength vs. depth, and to relate this information to the ice temperature and salinity. Ice thicknesses were measured at a total of 20 holes using drill hole and steam hole techniques. Measurements from the 2012 field program are unique because they provide the only available information about the keel strength of thick, hummocked multi-year ice below a depth of 10 m. Four offshore trips took place during the second field program the following year, from 16 March to 10 April, 2013 in Sachs Harbour, Northwest Territories. A total of 6 floes were visited, 4 tracking beacons were deployed on individual floes, and 37 drill-hole/steam-hole measurements were made to document the ice thickness. Strength measurements on multi-year ice were not obtained, as the 2013 field program was cut short due to funding constraints. The viability of a third field program for spring 2014 is currently under consideration. Sea ice thickness, salinity and temperature data are available in .xls and .csv formats. Sea ice strength data is not presented, please contact the Principal Investigator for further information.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.752
Threshold uncertainty score0.494

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.020
GPT teacher head0.225
Teacher spread0.205 · 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 designObservational
Domainnot available
GenreDataset

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
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Polar Data NetworkSame topicLand Rights and ReformsFrench-language works237,207