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Record W2193974218

Breaking the ice on the booster fan dilemma in US underground coal mines

2010· article· en· W2193974218 on OpenAlexaboutno aff
Anu Martikainen, Cliff D. Taylor

Bibliographic record

VenueMining Engineering · 2010
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Health and Safety Research
Canadian institutionsnot available
Fundersnot available
KeywordsBooster (rocketry)EngineeringCoalCoal miningAeronauticsMining engineeringForensic engineeringWaste management
DOInot available

Abstract

fetched live from OpenAlex

A.L. Martikainen is a research engineer and C.D. Taylor is an industrial hygienist at the National Institute for Occupational Safety and Health, Pittsburgh Research Laboratory, Pittsburgh, PA. Paper number TP-09-030. Original manuscript submitted June 2009. Revised manuscript accepted for publication May 2010. Discussion of this peer-reviewed and approved paper is invited and must be submitted to SME Publications by Jan. 31, 2011. Abstract booster fans increase air pressure to overcome resistance, the objective being to force adequate amounts of air through distant workings. they are used in areas that are difficult or uneconomic to ventilate with main fans alone. Booster fans are currently permitted in underground coal mines in some countries; the United Kingdom, South Africa, Australia and Canada have been defined as major users. Booster fans are not allowed in the US bituminous and lignite coal mining operations at the present time due to safety concerns. This paper presents the history of booster fan use in coal mines of the United States during the last 90 years. Changes in regulations, as well as advantages and disadvantages of booster fan use, are discussed. Research and petitions for booster fan use are highlighted in order to bring the debate into focus.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.072
Threshold uncertainty score0.457

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 integrity0.0000.001
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 head0.064
GPT teacher head0.400
Teacher spread0.336 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations3
Published2010
Admission routes1
Has abstractyes

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