MétaCan
Menu
Back to cohort
Record W4292427407 · doi:10.1063/5.0092416

Advancement in engineering materials and the growing concern

2022· article· en· W4292427407 on OpenAlexaff
Olusegun David Samuel, O.S.I. Fayomi, D. Olusanyan, Oluranti Agboola, N. E. Udoye, K. M. Oluwasegun

Bibliographic record

VenueAIP conference proceedings · 2022
Typearticle
Languageen
FieldEngineering
TopicElectrodeposition and Electroless Coatings
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsCorrosionCoatingMaterials scienceSurface engineeringNightmareDeposition (geology)Computer scienceConstruction engineeringRisk analysis (engineering)Manufacturing engineeringNanotechnologyMetallurgyEngineeringBusiness

Abstract

fetched live from OpenAlex

Corrosion has been and still the world's worst nightmare which costs hundreds and thousands of dollars for companies to maintain their equipment and repairs. Studies are being done all around the world to create the solution toward preventing the corrosion by surface engineering technology. One of the simplest and most cost effective methods to provide thin film coating for advance application is through electrolytic deposition route. Thus this review looks into the advances of materials and corrosion challenges.

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)0.003
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.019
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0030.004
Open science0.0010.002
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0190.007

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 head0.008
GPT teacher head0.200
Teacher spread0.191 · 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 designNot applicable
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

Citations1
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueAIP conference proceedingsSame topicElectrodeposition and Electroless CoatingsFrench-language works237,207