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Record W3175789774 · doi:10.1080/02670836.2021.1940670

Critical Assessment 40: A search for the eutectic system of high-temperature cast aluminium alloys

2021· article· en· W3175789774 on OpenAlexafffund
Frank Czerwiński

Bibliographic record

VenueMaterials Science and Technology · 2021
Typearticle
Languageen
FieldEngineering
TopicAluminum Alloy Microstructure Properties
Canadian institutionsNatural Resources Canada
FundersNatural Resources Canada
KeywordsEutectic systemMaterials scienceAluminiumMetallurgyEutectic bondingMelting temperatureAlloyComposite material

Abstract

fetched live from OpenAlex

A quest for the eutectic system of novel cast aluminium alloys, having high-temperature capabilities, is critically assessed with two potential candidates of Al–Al 3 Ni and Al–Al 11 Ce 3 examined and compared to the presently used Al–Si base. The conventionally cast Al–Al 3 Ni and Al–Al 11 Ce 3 eutectics do not exhibit the anticipated advantage over Al–Si in strengthening retention at temperatures up to 500°C. The promising differences between diffusivities of silicon, nickel, and especially cerium in aluminium, and eutectic melting temperatures, accompanied by high coarsening resistance of Al 3 Ni, Al 11 Ce 3 phases and the eutectic hardness retention are inconsistent with observed similarities in the temperature-related strengthening-reduction of all three eutectics. These findings will help defining the criteria for development of the eutectic system, suitable for future heat-resistant aluminium alloys.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.009
GPT teacher head0.249
Teacher spread0.239 · 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

Citations30
Published2021
Admission routes2
Has abstractyes

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