A comparison of the Bioscreen method and microscopy for the determination of lag times of individual cells of Listeria monocytogenes
Bibliographic record
Abstract
Lag phase durations (tLag) of individual Listeria monocytogenes cells were analysed using the NightOwl Molecular Imaging System, and results were compared with mean individual cell lag times (tL) obtained from the detection time (td) method using Bioscreen. With Bioscreen, an average tL of 6.39+/-0.89 h was obtained from five separate experiments. With the NightOwl method, an average tLag of 2.73+/-0.06 h was obtained from three experiments consisting of eight total replicates. Lag values from the NightOwl and Bioscreen are related by the equation: tLag = tL + DT, where DT is the doubling time. The equivalent tLag mean value for the Bioscreen method was 7.11+/-0.84 h. Individual lag times measured by both methods were normally distributed (r2 for Bioscreen and NightOwl ranged from 0.951 to 0.999 and from 0.884 to 0.982, respectively). The results suggest that the NightOwl method can provide accurate estimates of individual cell lag times, which will facilitate the development of combined discrete continuous models for bacterial growth.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".