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Record W4248873999 · doi:10.1037/e578902012-394

A Field Study of Haul Truck Operations in Open Pit Mines

2011· dataset· en· W4248873999 on OpenAlexafffund
Patrick Stahl, Birsen Donmez, Greg A. Jamieson

Bibliographic record

VenuePsycEXTRA Dataset · 2011
Typedataset
Languageen
FieldEngineering
TopicMining Techniques and Economics
Canadian institutionsUniversity of Toronto
FundersMitacsQueen's UniversityBarrick Gold Corporation
KeywordsTruckOpen-pit miningField (mathematics)Transport engineeringEngineeringMining engineeringAutomotive engineeringMathematics

Abstract

fetched live from OpenAlex

This paper presents findings from a field study of the operation of haul trucks in two open pit gold mines.Qualitative results relevant to the haul truck operator's work environment are presented, and the human factors challenges of the work are identified.Three specific issues that stood out from the study are discussed in detail.First, fatigue is identified as a major contributing factor to crashes and overall performance in open pit traffic, heightened by the specific work characteristics of a haul truck operator.Second, negative transfer is discussed as it interferes with the adaptation from one truck type to another: a consequence of inconsistent controls across different truck brands.Third, the under utilization of and the general posture of suspicion towards the dispatch system are reported, with a list of potential reasons related to automation characteristics.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.025
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.056
GPT teacher head0.311
Teacher spread0.255 · 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 designObservational
Domainnot available
GenreDataset

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

Citations2
Published2011
Admission routes2
Has abstractyes

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