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Record W2558632667 · doi:10.4043/27465-ms

Baffin Island Deep Water Arctic Port

2016· article· en· W2558632667 on OpenAlexaff
G.R. Watters

Bibliographic record

VenueArctic Technology Conference · 2016
Typearticle
Languageen
FieldEngineering
TopicOffshore Engineering and Technologies
Canadian institutionsCanadian Council of Professional Engineers
Fundersnot available
KeywordsPort (circuit theory)ScheduleArcticIron oreTonnageDOCKDeep waterEnvironmental scienceEngineeringCivil engineeringEnvironmental resource managementMining engineeringComputer scienceOceanographyGeologyMarine engineeringGeographyArchaeology

Abstract

fetched live from OpenAlex

Abstract Located 500 km north of the Arctic Circle, the massive Mary River Iron mine project required an operating ore dock to annually ship 3.5 million tonnes of iron ore to world markets. The high latitude Arctic ore dock loaded its first bulk carrier on August 8, 2015 from the its record breaking −17.75 m deep water berth. The project was executed by a design-build team selected by the owner after it became apparent the traditional design-bid-build method could not achieve schedule and budget objectives. Major challenges facing the design-build team included −35 degree celcius temperatures, 24- hour darkness, remote logistics, compressed schedule and varying geotechnical site conditions. To minimize risk in this challenging environment, the design-build team redesigned most of the project with a major focus on modularization of components in the south and utilization of a land-based construction methods rather than reliance on a fleet of marine equipment.

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)0.001
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.662
Threshold uncertainty score0.673

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0760.013

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 head0.007
GPT teacher head0.180
Teacher spread0.174 · 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".

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Citations0
Published2016
Admission routes1
Has abstractyes

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