MétaCan
Menu
Back to cohort

Mobile Harbor Crane Wheel Hub Fatigue Failure

2019· book-chapter· en· W4254707825 on OpenAlexaff
J. Shirokoff

Bibliographic record

VenueASM International eBooks · 2019
Typebook-chapter
Languageen
FieldEngineering
TopicMechanical Failure Analysis and Simulation
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsFatigue testingCorrosion fatigueCrackingStructural engineeringFatigue crackingCorrosionEngineeringFailure mechanismFracture (geology)Forensic engineeringMaterials scienceGeotechnical engineeringMetallurgyComposite material

Abstract

fetched live from OpenAlex

Abstract Failure analysis of a mobile harbor crane wheel hub that included SEM and EDS analyses demonstrated that the mechanism of failure was fatigue. The wheel hub was a ductile cast iron component that had been subjected to cyclic loading during a ten-year service period. The fracture surface of the fatigue failure also contained corrosion deposit, suggesting that cracking occurred over a period of time sufficient to allow corrosion of the cracked surfaces. Replacement and alignment of the failed wheel hub was recommended along with inspection of the nonfailed wheel hubs that remained on the crane.

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)0.000
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: Other · Consensus signal: Other
Teacher disagreement score0.032
Threshold uncertainty score0.106

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0320.009

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 head0.014
GPT teacher head0.226
Teacher spread0.212 · 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
GenreOther

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
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueASM International eBooksSame topicMechanical Failure Analysis and SimulationFrench-language works237,207