Minimum Inhibitory Concentration (MIC) versus Minimum Biofilm Eliminating Concentration (MBEC) in Evaluation of Antibiotic Sensitivity of Gram-negative Bacilli Causing Peritonitis
Bibliographic record
Abstract
OBJECTIVE: Minimum inhibitory concentration (MIC) and minimum biofilm eliminating concentration (MBEC) results were compared to determine changes in the pattern of antibiotic sensitivity of gram-negative bacilli from the planktonic to the biofilm phase of growth. METHODOLOGY: The MIC and MBEC assays were conducted on stored isolates obtained from patients presenting with peritoneal dialysis-related gram-negative peritonitis with Escherichia coli or Pseudomonas. RESULTS: The antibiotic sensitivities of planktonic organisms tested by the MIC assays were significantly higher than the antibiotic sensitivities of the same organisms in their biofilm state, as tested by the MBEC assays. CONCLUSIONS: In their biofilm state, gram-negative bacteria are much less susceptible to antibiotics compared to their antibiotic susceptibility in the planktonic state.
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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 | 0.001 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".