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Record W2043361448 · doi:10.1002/pamm.200510312

Non‐linear modelling and statistical anlaysis of multi‐stage high‐pressure inactivation of lactic acid bacteria

2005· article· en· W2043361448 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePAMM · 2005
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicrobial Inactivation Methods
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsLactococcus lactisDegree CelsiusLactic acidChemistryStreptococcaceaeBacteriaFood scienceMetabolic activityBiochemistryBiological systemBiologyThermodynamics

Abstract

fetched live from OpenAlex

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)

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.176
Threshold uncertainty score0.375

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.029
GPT teacher head0.313
Teacher spread0.284 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it