First Comprehensive Evaluation of the M.I.C. Evaluator Device Compared to Etest and CLSI Broth Microdilution for MIC Testing of Aerobic Gram-Positive and Gram-Negative Bacterial Species
Bibliographic record
Abstract
The M.I.C. Evaluator strip (Thermo Fisher Scientific, Basingstoke, United Kingdom) uses a methodology similar to that of Etest. In this first assessment of the M.I.C. Evaluator device, 409 strains of aerobic Gram-positive bacteria (staphylococci, streptococci, and enterococci) and 325 strains of Enterobacteriaceae, Pseudomonas species, and Acinetobacter species were tested by M.I.C. Evaluator strip, Etest, and broth microdilution as a reference standard. The Gram-positive bacteria included staphylococci (methicillin-resistant Staphylococcus aureus, methicillin-susceptible S. aureus, and coagulase-negative staphylococci), Streptococcus pneumoniae, beta-hemolytic streptococci and viridians group strains, vancomycin-resistant enterococci, and other enterococci. The Gram-negative bacteria included 250 strains of 60 Enterobacteriaceae species plus 50 Pseudomonas and 25 Acinetobacter species. A total of 14 antimicrobial agents (depending on the species) were included. The same methodology and reading format were used for M.I.C. Evaluator strips and Etest. Broth microdilution methodology was performed according to CLSI document M07-A8. For the clinical strains, >95% of results were plus or minus one doubling dilution for all species. There were fewer than 5% minor errors, fewer than 3% major errors, and fewer than 1% very major errors. M.I.C. Evaluator strips and Etest often reported higher MICs than the reference broth microdilution method. The M.I.C. Evaluator strips provided results comparable to those of the predicate Etest device and are of value for the accurate testing of MICs for these important pathogens.
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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 | 0.035 | 0.027 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".