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Record W2326299086 · doi:10.4043/otc-20298-ms

East Coast Canada R&D and Offshore Development in Northern Frontiers

2009· article· en· W2326299086 on OpenAlexaffabout
David William Finn

Bibliographic record

VenueProceedings of Offshore Technology Conference · 2009
Typearticle
Languageen
FieldEngineering
TopicOffshore Engineering and Technologies
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsFrontierArcticSubmarine pipelineInvestment (military)The arcticPetroleumScarcityBusinessEnvironmental resource managementEnvironmental planningEngineeringOceanographyEnvironmental scienceGeographyGeologyEconomicsPolitical science

Abstract

fetched live from OpenAlex

Atlantic Canada has seen the successful development of four major offshore projects in a technically-challenging frontier environment with high discovery and development costs. The response to the challenges of ice and a harsh operating environment have contributed to the growth of a significant R&D and engineering consulting capacity that is now being applied to projects in arctic, sub-arctic and other ice-covered regions. Although significant investment is being applied globally towards petroleum resource development in these environments, considerable technical challenges remain. A concerted R&D effort will be required to enable economic development of these resources. With the scarcity of arctic engineering and related capacity in the global R&D/engineering community, collaboration can minimize redundant research effort and share technology development risks and costs. This paper will present a review of some of the

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)0.002
metaresearch head score (Gemma)0.002
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: Empirical · Consensus signal: none
Teacher disagreement score0.967
Threshold uncertainty score0.240

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0040.002
Scholarly communication0.0050.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.009
GPT teacher head0.181
Teacher spread0.172 · 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
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
Published2009
Admission routes2
Has abstractyes

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