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 present article discusses an approach to training high-level athletes’ perceptual-cognitive skills. The intention herein is to (a) introduce concepts in regard to what may be required by athletes to optimally process sports-related visual scenes at the perceptual-cognitive level; (b) present an experimental method of how it may be possible to train this capacity in athletes while discussing the necessary features for a successful perceptual-cognitive training outcome; and (c) propose that this capacity may be trainable even among the highest-level athletes. An important suggestion is that a simple difference between sitting and standing testing conditions may strongly influence speed thresholds with this task, which is analogous to game movement dynamics in sports, indicating shared resources between such high-level perceptual-cognitive demands and mechanisms involved in posture control. A discussion follows emphasizing how a perceptual-cognitive training approach may be useful as an integral component of athletic training. The article concludes with possible future directions.
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 | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 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