MétaCan
Menu
Back to cohort
Record W2198181646 · doi:10.5539/jmsr.v5n1p89

Studies on Amorphous Alloy Dispersed Aluminium Matrix Composite Prepared by High Pressure Torsion

2015· article· en· W2198181646 on OpenAlexvenueno aff
S. Hembrom, B. N. Roy, Nidhi Khobragade, Debdas Roy

Bibliographic record

VenueJournal of Materials Science Research · 2015
Typearticle
Languageen
FieldEngineering
TopicAluminum Alloys Composites Properties
Canadian institutionsnot available
Fundersnot available
KeywordsMaterials scienceDifferential scanning calorimetryComposite numberAlloyAmorphous solidAluminiumComposite materialAluminium alloyThermal stabilityAmorphous metalScanning electron microscope6063 aluminium alloyMetallurgyChemical engineeringCrystallography

Abstract

fetched live from OpenAlex

<p class="1Body">Aluminium-based composite reinforced with Cu base amorphous alloy dispersed composite was prepared by means of high pressure torsion between a powder mix of aluminium and amorphous Cu base alloy. The X-ray diffraction pattern of powdered and consolidated composites shows the aluminium phase while the thermal stability of the amorphous alloy was studied with the aid of differential scanning calorimetry (DSC). The microstructural feature of the composite through scanning electron microscope reveals the well-distributed reinforcements in the host aluminium matrix. The hardness measurement on the as prepared composites shows significant increase in hardness with increase in reinforced amorphous alloy. Wear property of the synthesized composites were measured by using ball on plate wear tester which shows increase in wear resistance with increase in reinforced amorphous alloys.</p>

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 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)0.007
metaresearch head score (Gemma)0.001
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 score0.026
Threshold uncertainty score0.603

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.078
GPT teacher head0.366
Teacher spread0.288 · 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 teacher head, 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

Citations4
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Materials Science ResearchSame topicAluminum Alloys Composites PropertiesFrench-language works237,207