Evaluation of the contribution of media derived from various animal livers on the production of Lucilia sericata
Bibliographic record
Abstract
The effects of liver from different animals and agar- media on the production of Lucilia sericata (Meigen 1826) larvae were investigated to determine the best medium for producing larvae for wound therapy. The research was conducted in two phases. The best liver for generating L. sericata larvae was determined in the first phase, using media with beef, porcine, lamb, and chicken livers gelled with agar. In the first phase of the research, it was established that chicken liver was acceptable since the number of flies emerging from puparia was the highest at 80.75%. The preparation and content of the best medium for developing L. sericata larvae were determined in the second phase using chicken liver, raw, cooked, agar, and agar+salt. The number of flies emerging from puparia on the medium with chicken liver + salt + agar was 95.7% in the second phase, followed by 95% of flies coming out of the pupa in the medium prepared with chicken liver and agar. Finally, as the number of flies developing in these two mediums was not significantly different, we believe that the chicken liver and agar medium are most suitable for developing larvae.
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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 | 0.001 | 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".