Evaluation of shotcrete rock support systems in underground mines by a new non-intrusive technique
Bibliographic record
Abstract
Le beton projete est un systeme de support economique utilise dans plusieurs mines souterraines au Canada. Malgre son usage frequent dans l'industrie miniere, des problemes tels que le controle de la qualite et la mesure precise de l'epaisseur du beton projete sont d'actualites. Cet article presente les faits saillants d'une etude sur la faisabilite de l'auscultation des parois de beton projete a l'aide de la methode d'auscultation non destructive MSR (basee sur la reflexion d'ondes micro sismiques) developpee et brevetee par l'universite McGill. Une etude au laboratoire sur les proprietes dynamiques de deux types de beton projete, soit un type normal et un autre ayant la meme resistance, mais avec des fibres metalliques a ete effectuee. Les resultats de ces essais demontrent clairement qu'il faut s'attendre a obtenir des vitesses d'ondes de compression superieures dans le beton projete melange avec les fibres metalliques. Deux visites a une mine souterraine en Ontario (Canada) ont permis de verifier la faisabilite du concept et de determiner les demarches a suivre au sujet du developpement du systeme. Ce systeme d'auscultation nous a permis d'obtenir des resultats tres proches des mesures directes de l'epaisseur. En outre, le systeme MSR a l'avantage d'etre plus precis et moins dispendieux que les autres systemes d'auscultation presentement sur le marche.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".