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Record W2321146564 · doi:10.1515/htmp.2006.25.5-6.337

Beta Fleck and Segregation in Titanium Alloy Ingots

2006· article· en· W2321146564 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

VenueHigh Temperature Materials and Processes · 2006
Typearticle
Languageen
FieldEngineering
TopicAluminum Alloy Microstructure Properties
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMaterials scienceMetallurgyAlloyTitanium alloyBETA (programming language)TitaniumMaterials processing

Abstract

fetched live from OpenAlex

The segregation defect known industrially as "betafleck" occurs in most of the beta and alpha/beta alloys of titanium, arising in segregation during the solidification of the final vacuum arc remelted (VAR) ingot. In this work we use the data generated in Part I of this study to investigate the possible causes of the defect. We conclude that more than one mechanism is potentially operative. In highly alloyed material the defect mechanism is likely to be caused by a similar flow system to that responsible for the "freckle" defect in steels and superalloys: in the lower alloyed materials, it is more likely that the defect arises in the redistribution of equiaxial crystals in the large VAR final ingot liquid pool volume which is solidifying under low temperature gradients. In either case, the industrially-practical solution to the problem appears to lie in VAR melting with steeper temperature gradients at the solidifying interface. We also outline the future need for alloy design to take into account the difference in defect-forming potential of the different betastabilizing elements available for alloy formulation.

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 score0.017
Threshold uncertainty score0.582

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 head0.003
GPT teacher head0.164
Teacher spread0.161 · 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