Navigating Human Factors in Maritime Safety: A Review of Risks and Improvements in Engine Rooms of Ocean-Going Vessels
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
This study systematically examines the critical issue of human error within ship operations and maintenance, focusing on the challenges in fully integrating technology to enhance maritime safety on merchant vessels.The investigation into the root causes of human errors, alongside an understanding of accident causation, forms the basis of this research.This work aims to identify effective mitigation strategies to improve ship management and safety by scrutinizing marine accidents attributable to human negligence or unsafe technology use.An analysis of marine human factor literature from 2010 to 2022, employing traditional and Integrative Literature Review Analysis methods, highlights the vital role of collaboration among seafarers and the necessity of comprehensive training.The findings reveal that categories related to human factors significantly contribute to marine accidents.It is posited that focused attention on these categories and the enhancement of seafarers' competencies could lead to a notable reduction in incidents, thereby bolstering overall shipping and maritime safety.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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