Bibliographic record
Abstract
PURPOSE: To provide a collection of important terms in oculoplastic surgery, their etymology, current usage, and clarification of terms with overlapping or often misconstrued definitions. METHODS: Commonly employed terms in oculoplastic surgery were collected, and their etymologies were determined. The authors then examined how these terms are being currently used in the published literature to determine how closely their usage matched the origin of the terms, if any terms had developed multiple meanings, or if multiple terms were being used to describe the same concept. RESULTS: This article assembles in one area much of the important terms in oculoplastic surgery, highlighting how the etymology of the terms both links to their meanings as well as clarifies the appropriate usage of terms that have evolved to develop several different definitions. Special attention is placed on clarifying the correct definitions of closely related but distinct terms. CONCLUSIONS: Most terms in ophthalmology are used in a uniform manner across the literature with definitions closely matching their etymology, but some terms in oculoplastic surgery are being used in a potentially confusing overlapping manner and warrant clarification.
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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 | 0.010 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.013 | 0.014 |
| Science and technology studies | 0.003 | 0.014 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".