Evaluation of Superficial and Deep Specimens for Isolation and Identifi-cation of Bacterial Isolates from Diabetic Foot Infections.
Bibliographic record
Abstract
Worldwide, Diabetic foot infections (DFIs) are a major medical, social, and economic problem reaching epidemic proportions carrying the increased risk of complications.[1,2] About 25% of the diabetics have the risk of developing foot ulceration which is one of the leading cause of mortality and morbidity in developing coun-tries.2,3,4The most feared complication of in-fected diabetic foot ulcers is gangrene which results in amputations and occurs 10-30 times more often in diabetics. About one major am-putation in 30 seconds worldwide in diabetics and the elevated mortality at follow up, rang-ing from 13% to 40% at 1 year to 39% – 80% at 5 years requires urgent strategies towards prevention of foot ulceration and amputations.[3,5] Once the protective layer of skin is bro-ken, the deep tissues are exposed to bacterial infection that progresses rapidly.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".