The unassisted visual system on earth and in space
Bibliographic record
Abstract
Chuck Oman has been a guide and mentor for research in human perception and performance during space exploration for over 25 years. His research has provided a solid foundation for our understanding of how humans cope with the challenges and ambiguities of sensation and perception in space. In many of the environments associated with work in space the human visual system must operate with unusual combinations of visual and other perceptual cues. On Earth physical acceleration cues are normally available to assist the visual system in interpreting static and dynamic visual features. Here we consider two cases where the visual system is not assisted by such cues. Our first experiment examines perceptual stability when the normally available physical cues to linear acceleration are absent. Our second experiment examines perceived orientation when there is no assistance from the physically sensed direction of gravity. In both cases the effectiveness of vision is paradoxically reduced in the absence of physical acceleration cues. The reluctance to rely heavily on vision represents an important human factors challenge to efficient performance in the space 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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".