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Record W4320511356 · doi:10.2991/978-2-494069-31-2_97

Development and Application of Roof Support of Roadways in Mines

2022· book-chapter· en· W4320511356 on OpenAlexaff
Ke Xu

Bibliographic record

VenueAdvances in Social Science, Education and Humanities Research/Advances in social science, education and humanities research · 2022
Typebook-chapter
Languageen
FieldEngineering
TopicGeomechanics and Mining Engineering
Canadian institutionsMcMaster University
Fundersnot available
KeywordsRoofFrame (networking)Mine safetyEngineeringProduction (economics)Order (exchange)Labor intensityCivil engineeringConstruction engineeringRisk analysis (engineering)Mining engineeringForensic engineeringCoal miningBusinessWaste managementMechanical engineeringCoalEconomics

Abstract

fetched live from OpenAlex

Underground mining is always the most dangerous industry.The mines' inside support structures are always the most critical part of studying in order to increase safety.The inside roof support has three main categories: frame stand support, anchor rock bolt support and reserved column support.Each method has its own advantages, but the disadvantages are also inescapable; thus, using a single design would heavily impact field practice, safety measurements and economic benefits.Therefore, under the situation that current methods can hardly have a technical breakthrough, it is very necessary to have more profound studies to combine two or more methods organically to adopt each's good points and avoid shortcomings.In the end, it would increase the underground support results and safety.Also, it can save massive initial costs and further maintenance fees, reduce labour intensity, improve the working environment and increase production efficiency.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.003

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 head0.061
GPT teacher head0.388
Teacher spread0.327 · 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 designBench or experimental
Domainnot available
GenreMethods

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
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueAdvances in Social Science, Education and Humanities Research/Advances in social science, education and humanities researchSame topicGeomechanics and Mining EngineeringFrench-language works237,207