Non‐linear modelling and statistical anlaysis of multi‐stage high‐pressure inactivation of lactic acid bacteria
Bibliographic record
Abstract
Abstract It was the aim of this work to determine the combined effects of pressure, temperature, and co‐solvents on Lactococcus lactis , and to detect correlations between culture‐dependent and culture‐independent methods for assessment of cellular viability and sublethal injury. Therefore, the pressure induced inactivation of L. lactis MG 1363 was investigated in 21 buffer systems at a pressure range of 0.1 MPa to 600 MPa and a temperature range of 5 to 50 Grad Celsius. The inactivation was characterised by viable cell counts, stress resistant cell counts, membrane integrity, metabolic activity, and LmrP activity. By using Principal Component Analysis, correlations were detected between viable cell counts and metabolic activity as well as stress resistant cell counts and LmrP activity. Based on these correlations, a fuzzy logic model was formulated. The model uses two of the five physiological states as autonomous output variables. Input variables are pressure, temperature, application time and food systems. Latter fully describe the inactivation process of L. lactis correctly. (© 2005 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".