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Record W4308440721 · doi:10.3390/coatings12111685

Secondary Structures on the Friction Surface of Diamond-like Coating

2022· article· en· W4308440721 on OpenAlexaff
Иосиф Гершман, А. Е. Миронов, German Fox Rabinovich, T. I. Muravyеva, И. В. Шкалей, О. О. Shcherbakova, E. V. Torskaya, Sergey V. Fedorov, J.L. Endrino

Bibliographic record

VenueCoatings · 2022
Typearticle
Languageen
FieldMaterials Science
TopicDiamond and Carbon-based Materials Research
Canadian institutionsMcMaster University
FundersRussian Science Foundation
KeywordsCoatingMaterials scienceDiamondMetallurgyBall (mathematics)Dry frictionManganeseWear resistanceChromiumComposite materialGeometry

Abstract

fetched live from OpenAlex

Peculiarities of the formation of secondary structures on the surface of a diamond-like coating are studied on the example of a friction contact between a steel ball and a diamond-like coating. The friction surface was examined in various areas; the zone of wear products (the boundary of the friction track) and the original surface outside the friction area. It is shown that secondary structures with a high content of iron, nickel, manganese, chromium, and oxygen are characteristic of areas with the highest wear resistance. Such secondary structures are formed because of the intense interaction of the diamond-like coating with the steel of the ball during dry friction.

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)0.001
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 score0.005
Threshold uncertainty score0.996

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.018
GPT teacher head0.250
Teacher spread0.232 · 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.

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
Published2022
Admission routes1
Has abstractyes

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