Dynamic modeling of TENORM exposure risk during drilling and production
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
Exposure to Technologically Enhanced Naturally Occurring Nuclear Radioactive Material (TENORM) from oil and gas drilling and production activities can have effects on both the environment and workers involved in the industry. There is a significant lack of available information regarding dynamic modeling and risk assessment of TENORM occupational exposure in the oil and gas industry, and available studies show that workers in the field are at risk of being exposed to varying levels of radiation. This paper presents a methodology to bridge this knowledge gap by modeling workforce TENORM radiation exposure at different oil and gas operation stages. This was achieved by integrating SHIPP (System Hazard Identification, Prediction and Prevention) Methodology And Rational Theory (SMART approach). The SMART approach was applied to develop an integrated framework for TENORM occupational exposure risk assessment. Application of the proposed approach is illustrated with a scenario, and outcomes from modeling this scenario explain how system degraded as a function of safety barrier performance.
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.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| 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