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Record W3124923211 · doi:10.2749/sed008.045

Fatigue Research on High-Performance Steels in Canada

2005· book-chapter· en· W3124923211 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldMaterials Science
TopicEngineering and Material Science Research
Canadian institutionsnot available
Fundersnot available
KeywordsWeldabilityDuctility (Earth science)ToughnessMaterials scienceForensic engineeringPopularityMetallurgyEngineeringWeldingCreepPolitical science

Abstract

fetched live from OpenAlex

<p>Compared to conventional structural grade steels, high-performance steel (HPS) pro­vides higher strength, improved weldability, greatly enhanced fracture toughness, and comparable ductility, as well as having "weathering" properties. The improved char­acteristics of HPS are achieved through lower levels of carbon and other elements, in conjunction with advanced steel-making practices using either quenching and tem­pering or thermo-mechanical controlled processing. All of these properties make HPS highly desirable for bridge applications. Indeed, although its development spans only the past decade, it is rapidly gaining popularity for use in highway bridges and is be­coming more widely available. Although many highway bridges have already been put into service in the United States, Canada has yet to implement this technology in bridges. Nevertheless, it is anticipated that the use ofHPS will become common in the Canadian market in the near future.</p>

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.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.622
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.085
GPT teacher head0.322
Teacher spread0.236 · 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