MétaCan
Menu
Back to cohort
Record W4385805670 · doi:10.1115/1.862tsc_ch11

Conforming Rough Surface Models

2023· book-chapter· en· W4385805670 on OpenAlexaff
Yuri S. Muzychka, M. M. Yovanovich

Bibliographic record

VenueASME eBooks · 2023
Typebook-chapter
Languageen
FieldEngineering
TopicAdhesion, Friction, and Surface Interactions
Canadian institutionsUniversity of WaterlooMemorial University of Newfoundland
Fundersnot available
KeywordsMaterials scienceThermal contact conductanceJoint (building)ConductanceRough surfaceContact resistanceComposite materialSurface (topology)ThermalThermal resistanceStructural engineeringCondensed matter physicsEngineeringThermodynamicsMathematicsPhysicsGeometry

Abstract

fetched live from OpenAlex

In this chapter, we consider thermal contact resistance between conforming rough surfaces. Both elastic and plastic contacts are considered. Gap conductance models for filled and unfilled joints are discussed. Joint conductance models considering all resistances (contact and gap) that are presented. Finally, the methods for enhancing contact conductance using coatings, foils, polymers, greases, pastes, and phase change materials are examined. We only present the most useful approaches but provide discussion for other problems and models where applicable.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.003

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 head0.039
GPT teacher head0.217
Teacher spread0.178 · 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 designTheoretical or conceptual
Domainnot available
GenreOther

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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueASME eBooksSame topicAdhesion, Friction, and Surface InteractionsFrench-language works237,207