Bibliographic record
Abstract
Refraction is defined as the act of determining the focal condition (emmetropia or various ametropias) of the eye and its corrections by optical devices, usually spectacles or contact lenses. 1 It is one of the most important activities of the clinical work of optometrists and an indispensable variable to be considered in studies on vision.Refraction is a cause of avoidable blindness, being the second cause of blindness in less-developed countries (18%), after cataract (39%). 2 Likewise, refraction is the first factor to consider in cases of binocular and accommodative disorders and consequently the first condition treated in such cases.3 Furthermore, one of the main areas of research and innovation in Visual Sciences, refractive surgery, is aimed at minimizing refraction, at providing spectacle independence and consequently quality of life.4 Therefore, refraction is one of the most important variables to evaluate in studies on vision and consequently in studies on Optometry, as a branch of Visual Sciences.A great variety of studies evaluating the effect of some therapeutic approaches, the outcomes with different optical aids, the distribution of refractive errors in different areas of the world or how to evaluate the impact of refractive error in some vision-related abilities have been conducted and reported since many years ago.The current issue of
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 | 0.019 | 0.050 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.002 | 0.009 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.013 | 0.004 |
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".