La gestion des risques liés aux situations de co-activité dans la phase de planification des projets
Bibliographic record
Abstract
Tout projet comporte des dangers et sa reussite dependra notamment de la facon dont son responsable arrivera a cemer les risques potentiels et a reduire la gravite de leurs consequences. Les problemes majeurs rencontres dans des projets de bâtiment et de genie civil proviennent de la gestion preventive des accidents autant que de leurs consequences. En Europe continentale la loi exige que la gestion du risque soit prise en compte de facon prealable a la mise en oeuvre de toute action importante sur le site ou doit se realiser le projet conceme. Dans le futur, il y aura meme une obligation legale d'inclure, des la phase d'etude, la gestion du risque dans le management de projets. Un des risques des plus importants qu'il faudra gerer est celui de co-activite. Ce risque peut apparaitre quand au moins deux ressources, comme des soudeurs et des peintres, travaillent dans le meme lieu et en meme temps. Ce memoire propose une methode d'analyse et d'aide a la decision afin d' eviter ces risques lies aux situations de co-activite. L'enjeu de ce memoire est important car une telle analyse constitue un moyen essentiel de preserver la sante et la securite des travailleurs, sous la fonne d'un diagnostic en amont des facteurs de risques auxque ls ils peuvent etre exposes.
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 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 | 0.010 | 0.026 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".