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Record W2017902463 · doi:10.1139/t10-009

Quantitative prop support estimation and remote monitor early warning for hard roof weighting at the Muchengjian Mine in China

2010· article· en· W2017902463 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCanadian Geotechnical Journal · 2010
Typearticle
Languageen
FieldEngineering
TopicGeoscience and Mining Technology
Canadian institutionsnot available
FundersTai'shan Scholar Engineering Construction Fund of Shandong Province of China
KeywordsRoofCoal miningBeddingGeotechnical engineeringExcavationMining engineeringWeightingWarning systemSpan (engineering)BedGeologyCoalEngineeringEnvironmental scienceCivil engineeringWaste management

Abstract

fetched live from OpenAlex

The complex coal seam structure and hard roof at the Muchengjian Mine were studied, and the equivalent tensile strength of the roof was determined by a retrospective analysis of similar roof cave-ins. The prop spacing or number of hydraulic props required per unit area were obtained by analyzing the roof caving span and thickness. The early warning threshold bedding vertical separation velocity for hard roof caving at the Muchengjian Coal Mine was determined to be about 14 mm/day, and the newly invented “bedding separation remote monitoring system” (BSRMS) was used for the first time for early warning of a roof fall. A total of 48 trials of early warning roof weighting were performed at the Muchengjian Mine. It was found that not only were all the early warnings accurate, but the support system was also safe and reliable.

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)0.001
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.866
Threshold uncertainty score0.991

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 head0.012
GPT teacher head0.238
Teacher spread0.226 · 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