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Record W2076134739 · doi:10.1051/jp4:2005125121

Inspection of an end quenched plain steel Jominy bar with photothermal radiometric techniques

2005· article· en· W2076134739 on OpenAlexaff
Yonggang Liu, Natalie Baddour, Andreas Mandelis, C. Wang

Bibliographic record

VenueJournal de Physique IV (Proceedings) · 2005
Typearticle
Languageen
FieldEngineering
TopicThermography and Photoacoustic Techniques
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsRadiometric datingPhotothermal therapyMaterials scienceBar (unit)HardenabilityMetallurgyComposite materialOpticsGeologyRemote sensingNanotechnologyPhysics

Abstract

fetched live from OpenAlex

The effect of the cooling rate on hardness and thermal conductivity in a metallurgical Jominy bar made of AISI 1018 steel, by means of a water end-quenched heat treatment process without diffusion-controlled case depth, is studied with photothermal radiometry (PTR). It is concluded that our two PTR techniques, common-mode rejection demodulation (CMRD) and conventional 50% duty-cycle square-wave frequency scan, are sensitive to low hardness values and gradients, unlike the high values all previous photothermal studies have dealt with to-date. Both PTR methods have yielded an anti-correlation between thermal conductivity and microhardness in this case as in previous cases with heat-treated and diffusion-controlled case depth profiles. It is shown that the cooling rate strongly affects both hardness and thermal conductivity in the Jominy-bar heat-treating process.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.005
GPT teacher head0.208
Teacher spread0.203 · 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 designBench or experimental
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
Published2005
Admission routes1
Has abstractyes

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