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Record W3127850314 · doi:10.17580/em.2020.02.06

Classification of protective pillars toward higher safety and innovation in room-and-pillar coal mining

2020· article· en· W3127850314 on OpenAlexaff
С. А. Прокопенко, В.В. Семенцов, M. S. Dobrovolsky, E. V. Nifanov

Bibliographic record

VenueEurasian Mining · 2020
Typearticle
Languageen
FieldEngineering
TopicGeotechnical and Geomechanical Engineering
Canadian institutionsGeomechanica (Canada)
FundersTomsk Polytechnic University
KeywordsPillarCoalCoal miningMining engineeringHard coalProduction (economics)Process (computing)EngineeringWaste managementComputer scienceStructural engineeringEconomics

Abstract

fetched live from OpenAlex

During room-and-pillar mining, protective pillars of coal are usually left standing. The protective pillars differ in shape, size, process properties and extractability ratios of coal. The authors propose a classification of the protective pillars with respect to their structure and shape in order to estimate and predict their properties. The extractability ratios of coal are calculated for the initial rib pillars and panels at different final shapes of protective pillars. The protective pillars are ranked with respects to the coal extractability ratios. Such systematization of pillars enables selecting the best engineering solutions and innovative improvement of room-and-pillar mining in specific geological conditions toward enhanced safety and efficiency of underground coal production. The article is prepared in the framework of the Competitiveness Enhancement Program of the Tomsk Polytechnic University.

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)0.000
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.002
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.026
GPT teacher head0.223
Teacher spread0.196 · 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
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

Citations0
Published2020
Admission routes1
Has abstractyes

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