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Record W2712354857 · doi:10.1080/02670836.2017.1342019

Temper-treatment development to decompose detrimental martensite–austenite and its effect on linepipe welds

2017· article· en· W2712354857 on OpenAlex
Nazmul Huda, Yuquan Ding, A.P. Gerlich

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMaterials Science and Technology · 2017
Typearticle
Languageen
FieldEngineering
TopicMicrostructure and Mechanical Properties of Steels
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceTemperingMartensiteAusteniteMetallurgyFerrite (magnet)WeldingBase metalVoid (composites)Ductility (Earth science)Heat treatingComposite materialMicrostructureCreep

Abstract

fetched live from OpenAlex

A tempering cycle was developed via heat treatment to study the decomposition of detrimental martensite–austenite (MA). The heat treatment cycle was found to preferentially decompose hard MA with a critical size of ≥1 µm, which decreases the hardness of these microconstituents after tempering at 300°C for 10 min. The dislocation density inside the MA and in the surrounding matrix was also decreased. Tempering of the X80 weldments containing MA reveals a similar decomposition behaviour. During transverse weld tensile testing of welds, a fracture occurred in the heat-affected zone due to void formation at the MA/ferrite interfaces. However, a fracture occurred in base metal with improved strength and ductility after tempering, in comparison to the fracture in the heat-affected zone of as-welded samples.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.034
Threshold uncertainty score0.461

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 head0.234
Teacher spread0.224 · 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