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
After baseline measurements in-lab, participants were sent home to train for several months (subacute (SA): 4.9±0.6 months [mean ± SD]; chronic (CH): 6.8±4.0 months). They used their personal computers with a chin/forehead-rest provided by the lab, which they were instructed to position 42cm away from their display during training. Participants performed 300 trials of their assigned training tasks (Static, Motion or Flicker) per location per day, at least five days per week, and they emailed their data log files back to the lab for analysis every week. During home training sessions, they were instructed to stay fixated on the fixation spot and warned that inadequate fixation accuracy could limit recovery.Session thresholds were calculated by fitting a Weibull function with a 72.5 percent correct performance threshold criterion. After participants’ thresholds improved consistently for at least 20 sessions, we moved their training stimulus 1˚ deeper into the blind field along the x-axis (Cartesian coordinate space). Because the diameter of the stimulus is 2.5 ˚, the new training location had ~80% overlap with the original training location.<i> </i>Once participants trained for about 4 months, with at least one improved location (defined as consistently good contrast thresholds at that location), they were brought back to the lab, and performance at all home-trained locations was verified with eye tracker-enforced fixation control. We aimed for a similar number of training sessions at the blind-field locations of interest before scheduling people to return for in-lab performance verification. However, the amount of time elapsed until the return visit did vary, as it was affected by the individual’s rate of improvement, their work/family schedules, and ability to travel to our single study site (participants originated from across the entire United States and Canada). All participants were best corrected using glasses or contact lenses during testing and training. The Research Subjects Review Board approved study procedures at the University of Rochester, which were conducted as per the Declaration of Helsinki, with written informed consent obtained from each participant, and participation was voluntary.<br>
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 | 0.002 | 0.076 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.006 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.293 | 0.461 |
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