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Record W3004750599 · doi:10.1002/adem.201901318

The Ignition Behavior of a Ternary Mg–Sr–Ca Alloy

2020· article· en· W3004750599 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAdvanced Engineering Materials · 2020
Typearticle
Languageen
FieldMaterials Science
TopicMagnesium Alloys: Properties and Applications
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaConsejo Nacional de Ciencia y Tecnología
KeywordsMaterials scienceAlloyOxideTernary operationIgnition systemMetallurgyComposite numberSubstrate (aquarium)Ternary alloySurface-area-to-volume ratioVolume (thermodynamics)Chemical engineeringAnalytical Chemistry (journal)Composite materialThermodynamicsChemistryChromatography

Abstract

fetched live from OpenAlex

In this work, a Mg–Sr–Ca alloy is evaluated for ignition resistance. The simultaneous use of Sr and Ca results in an ignition temperature increase of ≈110 °C compared to pure Mg. This is attributed to the formation of a compact oxide scale due to the modification of the native MgO scale. A new parameter, the effective Pilling–Bedworth ratio (EPBR), which is the molar volume ratio between the oxide formed and the substrate alloy, is developed. The EPBR of the composite oxide forming on the Mg–Ca–Sr alloy is found to be greater than 1, resulting in a protective scale due to the increased volume occupied by the oxide at the surface. In the solid state, the oxide scale is rich in CaO, with the SrO contribution being minimal. In the liquid state, SrO contribution increases.

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 score0.007
Threshold uncertainty score0.521

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 head0.012
GPT teacher head0.214
Teacher spread0.202 · 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