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Record W2059507605 · doi:10.1179/026708401225001273

Morphology and Nanoindentation Profiles of Automotive Engine Components

2002· article· en· W2059507605 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSurface Engineering · 2002
Typearticle
Languageen
FieldEngineering
TopicLubricants and Their Additives
Canadian institutionsImperial Oil (Canada)University of Alberta
Fundersnot available
KeywordsNanoindentationMaterials scienceComponent (thermodynamics)Composite materialMorphology (biology)Scanning electron microscopeLubricityAutomotive engineSurface (topology)Automotive engineeringGeometryEngineering

Abstract

fetched live from OpenAlex

Scanning probe microscopy has been used for the analysis of a wear surface from a component removed from a heavy duty diesel engine. This component is analysed and compared to a wear surface that has been generated in a rig that simulates engine conditions. It was found that the wear surface from the engine component is highly pitted in the regions where contact pressures are exceedingly high, whereas regions further away from the high pressure points are covered with an anti-wear film that resembles the films formed in the wear rig. These results are confirmed by both scanning force microscopy images and nanoindentation results.

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)0.000
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.146
Threshold uncertainty score0.510

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 head0.010
GPT teacher head0.184
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