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Record W6929202062 · doi:10.4224/12340988

Scoping study: ice information requirements for marine transportation of natural gas from the High Arctic

2005· report· en· W6929202062 on OpenAlexaffvenueabout

Bibliographic record

VenueNPARC · 2005
Typereport
Languageen
FieldComputer Science
TopicError Correcting Code Techniques
Canadian institutionsNational Research Council CanadaEnvironment and Climate Change CanadaCanadian Wood Council
Fundersnot available
KeywordsArcticSea iceMarine transportationKey (lock)The arcticInformation system

Abstract

fetched live from OpenAlex

This report describes a scoping study that was performed to investigate methods for improving transportation in the High Arctic. Fourteen Captains of ice-class vessels were interviewed. They unanimously said that the detection and avoidance of multi-year ice was the key issue. They also indicated that better knowledge of regions where ice pressure and leads develop is important. A one-day Workshop was held with several key Stakeholders and issues related to improved systems were discussed. This report summarizes these findings as well as reviews the existing ice information systems, the Canadian Ice Service operations, and the use of ice information by the Canadian Coast Guard. A three-year program is suggested that would significantly improve detection of multi-year ice.

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)0.028
metaresearch head score (Gemma)0.094
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.964
Threshold uncertainty score0.147

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0280.094
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.006
Science and technology studies0.0020.001
Scholarly communication0.0030.003
Open science0.0010.002
Research integrity0.0020.001
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 head0.038
GPT teacher head0.317
Teacher spread0.280 · 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
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

Citations1
Published2005
Admission routes3
Has abstractyes

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