Breaking the ice on the booster fan dilemma in US underground coal mines
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.008 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".