Laser scanning analysis of cold cataract in young and old bovine lenses.
Bibliographic record
Abstract
PURPOSE: This research involves the use of a laser scanning instrument to evaluate the formation of cold cataracts in young and older bovine lenses. METHODS: Bovine lenses from 18 (n=14) week old calf eyes and approximately 10 (n=7) year old animals were extracted in a sterile environment. The lenses were placed in a specialized glass chamber with temperature controlled circulating culture medium. The temperature cycle inside the chamber started at 37 degrees C, slowly cooled to 4 degrees C, and then warmed back up to 37 degrees C. A laser scanning system (ScanTox) was used to analyze the optical quality of bovine lenses during a cooling and warming cycle. RESULTS: The relative light transmittance was measured as a function of pixel excitation caused by refracted beams and compared to pre-treatment measures. Each lens from each age group showed a significant decrease in transmittance at 4 degrees C, which recovered when the lenses were warmed to 37 degrees C. Lenses from young eyes showed less loss of refracted beam intensity than lenses from older eyes (32% versus 34%), although the difference was not significant. CONCLUSIONS: The results of the present study indicate cold cataracts can be induced in both old and young bovine lenses, as shown by using a scanning laser instrument.
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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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".