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Record W6966690461 · doi:10.4224/40000399

The Tibbitt to Contwoyto winter road in the NWT: identification of available data and research needs

2011· report· en· W6966690461 on OpenAlexaffvenueabout

Bibliographic record

VenueNPARC · 2011
Typereport
Languageen
Field
Topic
Canadian institutionsNational Research Council CanadaCanadian Wood Council
Fundersnot available
KeywordsIdentification (biology)Quality (philosophy)Joint ventureJoint (building)Range (aeronautics)Flooding (psychology)Ice formation

Abstract

fetched live from OpenAlex

Information on the Tibbitt to Contwoyto Winter Road north of Yellowknife was acquired by the author during a three-day field trip in March 2008. The construction and maintenance of this road, most of which is constructed over frozen lakes, is managed by the Joint Venture Management Committee (JVMC). It is a major access road to supply several mine sites. Build-up initiation occurs in December. When the ice thickness is deemed adequate, crews get on the ice with light vehicles. EBA engineers are in charge of design ice thickness, so as to ensure they can meet minimum ice thickness criteria. Flooding with pumps is used to improve ice surface quality and also increases the thickness of the ice cover. The ice road is a public-private road. Permitted speeds range from 10 to 35 km/h, but can go up to 60 km/h on expressways. Outstanding issues raised by JVMC include means of extending the season, how to mitigate the effects of blow-outs, and what is the role of load-induced crack accumulation.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.838
Threshold uncertainty score0.322

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.009
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0130.004

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 head0.313
GPT teacher head0.418
Teacher spread0.105 · 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

Citations2
Published2011
Admission routes3
Has abstractyes

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