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Record W4303621787 · doi:10.53063/synsint.2022.23118

On the synthesis and sintering behavior of a novel Mg-Ca alloy, Part I: Mechanical alloying

2022· article· en· W4303621787 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueSynthesis and Sintering · 2022
Typearticle
Languageen
FieldMaterials Science
TopicMagnesium Alloys: Properties and Applications
Canadian institutionsnot available
FundersMaterials and Energy Research Center
KeywordsCrystalliteDiffractometerMaterials scienceAlloyScanning electron microscopeScherrer equationSinteringMetallurgyNanocrystalline materialComposite materialNanotechnology

Abstract

fetched live from OpenAlex

A novel Mg-0.7Ca alloy was prepared by the mechanical alloying (MA) process. Different variables were examined in order to obtain the optimum sample with the best milling behavior and potential sinterability. The structural studies were carried out using X-ray Diffractometer (XRD) and scanning electron microscopy (SEM). Crystallite size and lattice strain of the milled samples were examined by Scherrer and Williamson-Hall methods in order to finalize the investigation.
 The optimum milling time was found to be 60 minutes. In addition, a starch-containing sample with a fraction of 2.5 weight percent seemed to have the best microstructural properties, based on SEM observations and crystallite size assessments. Due discussions about the effective phenomena during the mechanical alloying were also included.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.013
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.041
GPT teacher head0.241
Teacher spread0.200 · 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