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Record W2064359606 · doi:10.1177/0954409712447170

Friction management on a Chinese heavy haul coal line

2012· article· en· W2064359606 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.

Bibliographic record

VenueProceedings of the Institution of Mechanical Engineers Part F Journal of Rail and Rapid Transit · 2012
Typearticle
Languageen
FieldEngineering
TopicRailway Engineering and Dynamics
Canadian institutionsL.B. Foster Rail Technologies (Canada)
Fundersnot available
KeywordsTonnageLubricationRail networkCoalRADIUSEngineeringAutomotive engineeringMechanical engineeringGeologyComputer scienceTransport engineering

Abstract

fetched live from OpenAlex

Shuohuang Railway (SHR) is one of the major coal carriers in China, with a total network length of 590 km running from Shenchi to Huanghua. Significant increases in annual operating tonnage have generated accelerated rail wear and rolling contact fatigue (RCF) growth problems for many sharper/lower radius curves. In order to address these rail problems, SHR is interested in the state-of-the-art total friction management (TFM) technology currently deployed by some North American heavy haul freight railroads and is evaluating the impact of TFM via a field trial at SHR’s Yuanping subdivision. This paper presents an evaluation of the effect of TFM, which includes both wayside gauge face lubrication and wayside application of a thin film top of rail friction modifier on control of lateral forces, rail wear and RCF.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.205
Threshold uncertainty score0.492

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 head0.007
GPT teacher head0.195
Teacher spread0.187 · 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