Bibliographic record
Abstract
Abstract A comparative evaluation study of the Bio-Rad® iQ-Check™Listeria monocytogenes II Kit (Bio-Rad Laboratories, Hercules, CA) was conducted at Q Laboratories, Inc., Cincinnati, OH. iQ-Check is a rapid method based on real-time PCR amplification and detection of L. monocytogenes in food and environmental samples. The iQ-Check method was compared to the Health Canada MFHPB-30 reference method for the analysis of five ready-to-eat meats—deli turkey, hot dogs, liver paté, raw fermented sausage, and deli ham—and one stainless steel surface. Each food matrix was analyzed at two contamination levels: a low level at 0.2–2 CFU/25 g and a high level at 2–5 CFU/25 g. The environmental surfaces were analyzed at a low level of 0.2–2 CFU/5 cm2 sampling area and a high level of 2–5 CFU/5 cm2 sampling area. There were 20 replicates per contamination level and five control replicates at 0 CFU/25 g or 0 CFU/5 cm2 sampling area (uninoculated). All samples detected by iQ-Check were subsequently confirmed by reference method protocol. There was no significant difference in the number of positive samples detected by the iQ-Check Listeria monocytogenes II Kit in comparison to the Health Canada MFHPB-30 method for all matrixes tested.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".