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Record W4302496058 · doi:10.5957/icetech-2008-112

Icebreaking Ore Carrier Project for Baffinland Iron Mines Corporation

2008· article· en· W4302496058 on OpenAlexaffabout
Göran Wilkman, Matti Arpiainen, Riku Kiili, Tom Mattsson, Rod Cooper, John T. Stubbs

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicOffshore Engineering and Technologies
Canadian institutionsLa Coop Fédérée
Fundersnot available
KeywordsInletBallastIron oreMarine engineeringShorePort (circuit theory)EngineeringEnvironmental scienceOceanographyGeologyMining engineeringMechanical engineeringArchaeologyGeography

Abstract

fetched live from OpenAlex

Baffinland Iron Mines Corporation is planning to utilize the iron deposits on the northern Baffin Island (Canada). The iron ore was discovered in the beginning of 1960ies. The mine is 100-142km from the sea shore (Milne Inlet or Steensby Inlet). The sea area from Milne Inlet and Steensby Inlet to North Atlantic is most of the year ice covered. Open water period may be only three months, from July to October. The operation is planned to be year-round. The amount of iron ore to be transported in the beginning of the production in 2014 is c. 18 million tonnes/year. The ore carriers are to be operated independently without icebreaker assistance. The ore carriers are assumed to operate at full draught both in loaded and ballast condition when operating in ice. The ship size was selected to be of main dimensions as a Dunkirkmax/Capesize vessel. There are two basic ore carrier alternative designs; The first alternative is conventional icebreaking vessel, which mainly operates by breaking ice with the bow. The second alternative is the so called Double Acting Ship (DAS). In the DAS concept the vessel is designed to operate bow first most of the time, in open water and in light ice conditions, but in severe ice conditions running astern. This paper describes the design process of the vessels including the basic requirements, operational conditions, transit simulations, model tests and the vessel designs.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.203
Threshold uncertainty score0.384

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.023
GPT teacher head0.216
Teacher spread0.193 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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
Published2008
Admission routes2
Has abstractyes

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