Análisis de riesgo ambiental aplicado a una empresa de almacenamiento y distribución de gases industriales
Bibliographic record
Abstract
[EN] Through this thesis will be developed an Environmental Risk Analysis in a company dedicated to the storage and distribution of industrial gases, located in the municipality of Puçol - Valencia, specifically in the Campo Aníbal industrial estate. According to comply with Law 26/2007 of October 23 of Environmental Responsibility, and being an industry that is subject to the application of Royal Decree 1254/1999, of July 16, by which the control measures were approved of the risks inherent in major accidents with hazardous substances. This law is intended to regulate the responsibility to prevent, avoid and repair environmental damage, in accordance with Article 45 of the Constitution and with the principles of prevention and "polluter pays". The cause of the pollution, even if it has not committed any administrative infraction, will be in charge of the total restoration of the environmental impact, reason why it will not be a mere economic indemnification. Using the methodology proposed by MAPFRE in the third quarter of 2007, which includes the analysis of sources of risk, primary control systems, transport system and vulnerable receivers, an Environmental Risk Value or Index will be obtained. This will allow the risk assessment as a post-analysis process, through which a decision is made, in areas to reduce or eradicate the risks analyzed that generate considerable environmental damages. Such as, environmental risk analysis, risk, frequency / probability, accidental scenario. In conclusion, by means of this thesis, it is expected that the companies of storage and distribution of industrial gases increase both the safety of industry and the environment, based specifically on the protection of the environment.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".