Recent remote underwater surveys: Advances in methods and technologies for structural assessments of dams and spillways
Bibliographic record
Abstract
Cet article présente les progrès récents des technologies et des méthodes pour les relevés structurels sous-marins des barrages. Deux cas réels seront présentés. Le premier concerne l’examen en cours d’un déversoir d’un grand barrage canadien en érosion, au moyen de sonar multifaisceaux, de photogrammétrie, de laser et de vidéo HD. En particulier, les processus de calcul de la perte volumétrique de matière érodée sont discutés. La présentation couvre des questions telles que la portée et la résolution du sonar, le positionnement, la navigation, les méthodes hydro-acoustiques et autres pour la détection des fuites, ainsi que les défis logistiques rencontrés lors de la collecte de données sur le terrain. Des exemples de rendus sonar et d’autres méthodes de rapport sont également présentés.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.008 |
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".