TNO Contribution to the Quest 303 Trial - Human Performance Assessed by a Vigilance and Tracking Test, a Multi-Attribute Task, and by Dynamic Visual Acuity (TNO Bijdrage aan het Quest 303 Onderzoek)
Bibliographic record
Abstract
A multi-national sea trial on the effects of ship motions on human performance was performed off the coast of Canada, in early 2007. Primary goal: To obtain subjective and objective measures for human task performance, possibly affected by real ship motion. TNO participated with a Vigilance and Tracking Test, a Multi-Attribute Task, and a Dynamic Visual Acuity test. The experiment was conducted in three phases: a pre-exposure phase in harbour, an exposure phase at sea, (sea conditions varying from calm to low sea state six) and a post-exposure phase in sheltered waters to re-examine baseline performance. Experiment schedule and protocol are described, motions and wave conditions encountered during the trial, and the results of the Dutch tests are presented. Results: Cognitive performance and visual acuity are impaired by ship motion. This seems to be caused by seasickness in particular, possibly even more so than by ship motion per se. Tracking was affected only by sickness, and not by motion itself. Apart from showing that DVA is of value to further quantify human performance, these data also support the development of an onsite fit-to-perform screening tool based on DVA.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".