Calculation of the Significance of Hazard Causative Factors
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.
Bibliographic record
Abstract
The paper is devoted to the actual problem of the estimation of hazard casual factors significance. Indices characterizing the significance of hazard casual factors in the occurrence of elementary undesirable events at potential hazard facility are proposed as well as indices of significance factors in accident occurrence. Algorithms for such calculation are described. Proposed indices are not alternative to probabilistic safety assessment indices but afford additional opportunity for analysis. Required precedent conditions for the significance indices calculation are described: knowledge base about factors and their impact on basic events occurrence made by the Method of Expert Evaluation Scales; formalized description of relations between basic events and an accident in the disjunctive-normal form; description of the situation when the situational significance of casual factors has to be calculated. The proposed indices can be used during the analysis of hazard casual factors. The algorithms proposed for the calculation of significance indices orient for developers of situational emergency centers, automated systems for hazard analytic at potential hazard facilities, particularly analytic systems of business projects when hazard technology is used.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it