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Record W4408164435 · doi:10.1080/19236026.2025.2450199

Suggested methodology for evaluating heading face stability and face support design options

2025· article· en· W4408164435 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCIM Journal · 2025
Typearticle
Languageen
FieldComputer Science
TopicFace recognition and analysis
Canadian institutionsWorkplace Health, Safety and Compensation Commission
Fundersnot available
KeywordsHeading (navigation)Face (sociological concept)Computer scienceStability (learning theory)EngineeringSociologyAerospace engineeringMachine learning

Abstract

fetched live from OpenAlex

Falls of ground and rockbursts are the main causes of death and serious injury in underground mines. To achieve the goal of “zero harm,” injuries should not be ignored. This article serves as reference material to assist mining operations to: 1) develop a process to evaluate heading face stability advanced using drill-and-blast methods while considering the level of equipment/mechanization used and mining practices; 2) develop face support standards to be implemented based on identified and assessed potential hazards associated with the stability of heading faces and worker safety; and 3) provide face support options based on the types of possible failure modes in low- and high-stress rock mass conditions in massive, jointed, and heavily jointed rocks.

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)0.004
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: Methods · Consensus signal: Methods
Teacher disagreement score0.910
Threshold uncertainty score0.351

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
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 integrity0.0000.000
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 head0.300
GPT teacher head0.434
Teacher spread0.134 · 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