Microfiltration of brilliant blue G dye.
Bibliographic record
Abstract
BACKGROUND: Brilliant blue G (BBG) is a safe and effective dye used to highlight the internal limiting membrane during macular surgery. The authors proposed that the utilization of a 0.22-μm filter intraoperatively can reduce the risk of inoculating an eye with contaminated BBG. METHODS: An in vitro model of contaminated BBG was prepared. Laboratory stock cultures of 7 organisms including, Staphyloccocus epidermidis, Streptococcus pneumoniae, Staphyloccocus aureus, Haemophilus influenza, Klebsiella pneumoniae, Fusarium species, and Candida albicans, were prepared in five 10-fold dilutions and injected into BBG vials. These mixtures were drawn with either a 5-μm filter, 0.22-μm, or without a filter and cultured on appropriate plates and growth conditions. RESULTS: No culture plates that had inoculate drawn through a 0.22-μm filter showed evidence of growth. There was evidence of growth for all organisms when no filter was used. A 5 μm was insufficient to filter Fusarium species. CONCLUSION: Using a 0.22-μm filter in the intraoperative processing of BBG would likely reduce the risk of infectious endophthalmitis resulting from contaminated dye.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".