Bibliographic record
Abstract
Historical Preamble When I arrived in Cambridge in the late 1970s to work with the late Fergus Campbell, the notion of critical periods for visual development was already well established through the seminal works of Hubel and Wiesel (1967), Blakemore (1976), and others (see Daw, 1995). The clinical implication of this was also recognized, namely, that visual improvements from the patching treatment of amblyopia were likely to be strongly age dependent and ineffective after the age of 7 to 8 years. At that time, the wisdom of Sir Stewart Duke-Elder held sway: “for patching to work it needs to be total and complete, day and night.” Fergus always felt that the stronger the statement, the more likely it was to be wrong. In fact, at that time, I remember his method for choosing research projects for graduate students. He would go to his bookshelf and choose at random one of Duke-Elder's System of Ophthalmology volumes, open it at random and locate a definitive statement on some visual topic. “Let's show this is wrong,” he would say, and the die was cast for what usually turned out to be another fruitful piece of research. Fergus felt that some form of active stimulation would be better than the passive viewing that resulted from patching. He was enamored with the idea of the visual cortex as a spatial frequency analyzer, and because my early results suggested amblyopes suffered from severe spatial distortions (Hess et al., 1978), his first suggestion for a new therapy was to show a single spatial frequency at sequential orientations to help their visual cortex “sort out” what we hypothesized were anomalous interactions between these spatial analysers.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".