Bibliographic record
Abstract
Abstract Excess workplace fatigue is a risk to safe operations and has been recognized as a contributing factor in recent industry incidents including Texas refinery explosion. API Recommended Practice 755 now requires refineries, petrochemical and chemical operations, natural gas liquefaction plants, and other facilities such as those covered by the OSHA Process Safety Management Standard to establish Fatigue Risk Management System (FRMS) policies and procedures. Chevron has implemented programs for refining and chemicals operations to address the risk of fatigue and is in the process of expanding these guidelines to cover other operations as well. The scope of FRMS guidelines includes workers on rotating shifts, extended hours/days, or callouts and those involved in process safety sensitive actions. Chevron existing pilot programs in select operating units in its U.S. Refineries, Upstream Gas Plants and Chemical Plants. Upon completion of the pilot programs, the FRMS system will be deployed in the remaining Process Safety Managed facilities in the United States and refineries in Canada and South Africa. The following areas are addressed based on guidelines: (1) Staffing Workload Analysis – performing initial and periodic assessment of the staffing balance; (2) Hours of Service Limits – establishing management exception processes and compliance; (3) Employee/ Supervisor Training – identifying causes, risks and potential consequences of fatigue and recognizing at risk employees; (4) Fatigue in Incident Investigation – determining if fatigue is a root cause or contributing to incidents; (5) Work Environments – determining changes that can affect alertness and fatigue risk and (6)Prevention and Management of Medical Conditions - providing sleep disorder screening and support resources. Next steps include evaluating how the FRMS guidelines may apply to Chevron's global workforce. Our international locations include off-shore production platforms, camps and shipping vessels where employees may work 12-hr. shifts for 28 days on/28 days off. The next wave of this project will determine which of the identified guideline areas will apply to each of these locations.
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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.043 | 0.010 |
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".