MétaCan
Menu
Back to cohort
Record W2161917594 · doi:10.1115/1.1454106

The Coefficient of Friction During Hot Rolling of Low Carbon Steel Strips

2002· article· en· W2161917594 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Tribology · 2002
Typearticle
Languageen
FieldEngineering
TopicMetallurgy and Material Forming
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSTRIPSTorqueMaterials scienceCarbon steelCoefficient of frictionStrip steelRolling resistanceFriction coefficientComposite materialMechanicsMetallurgyThermodynamicsPhysics

Abstract

fetched live from OpenAlex

Hot rolling tests were performed on low carbon steel strips with the objective of determining the coefficient of friction as a function of the process variables. The growth of the scale prior to rolling was controlled and the thickness of the layer of scale at the entry remained in the range of 20–100 μm, somewhat higher than in the finishing train of a hot strip mill. Roll separating forces, roll torques, the speed, the reduction and the entry temperature were monitored. The effective coefficient of friction was determined by using a one-dimensional model of the flat rolling process. The coefficient was chosen to allow matching the measured and calculated roll force and the roll torque. An empirical relation, connecting the coefficient of friction to process variables was obtained by non-linear regression analysis.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.115
Threshold uncertainty score0.183

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.010
GPT teacher head0.191
Teacher spread0.181 · 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