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Record W4298455864 · doi:10.5957/icetech-2012-115

Determining Feasibility of Using an Open Water Mobile Offshore Drilling Unit in the Chukchi Sea

2012· article· en· W4298455864 on OpenAlexaff
Randall Shafer, Khalid Soofi, Peter G. Noble, C. Yetsko

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsConocoPhillips (Canada)
Fundersnot available
KeywordsSubseaDrillingOffshore drillingSubmarine pipelineOpen waterGeologySea iceEnvironmental sciencePetroleum engineeringOceanographyEngineering

Abstract

fetched live from OpenAlex

ConocoPhillips was awarded Chukchi Sea leases in February 2008. The initial assumption for Exploration drilling was to use a drillship with a Subsea Blowout Preventer. This is how the previous five Chukchi Sea wells were drilled in 1989, 1990, and 1991. An average open water season, approximately 100 days, and ice alerts advancements, primarily detection based, would allow the use of different type Mobile Offshore Drilling Unit (MODU). This paper will describe how hazardous ice was defined for a particular MODU and its associated ice alerts system. Key areas of focus will be the use of high resolution radar in detecting hazardous ice, delineation of the open water season and planned ice alerts system.

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)0.003
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.086
Threshold uncertainty score0.172

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.094
GPT teacher head0.313
Teacher spread0.218 · 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

Citations0
Published2012
Admission routes1
Has abstractyes

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