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Record W90860557 · doi:10.1093/jaoac/89.1.115

Comparison of the Compact Dry CF with the Most Probable Number Method (AOAC Official Method 966.24) for Enumeration of Coliform Bacteria in Raw Meats: Performance-Tested MethodSM 110401

2006· article· en· W90860557 on OpenAlexaff
Hidemasa Kodaka, Hajime Teramura, Tadanobu Nirazuka, Shingo Mizuochi, David Goins, Joseph Odumeru, Yataro KOKUBO

Bibliographic record

VenueJournal of AOAC International · 2006
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBacterial Identification and Susceptibility Testing
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsEnumerationFood scienceRaw milkColiform bacteriaFecal coliformMathematicsBacteriaBiologyChemistryEnvironmental scienceWater qualityEcology

Abstract

fetched live from OpenAlex

Compact Dry CF is a ready-to-use test method for the enumeration of coliform bacteria in food. The plates are presterilized and contain culture medium and a cold water-soluble gelling agent. The medium should be rehydrated with 1 mL diluted sample inoculated into the center of the self-diffusible medium, allowing the solution to diffuse by capillary action. The plate can be incubated at 35 degrees C for 20-24 h and the colonies counted without any further working steps. The Compact Dry CF medium plates were validated with 5 different raw meats. The performance tests were conducted at 35 degrees C. In all studies performed, no apparent differences were observed between the Compact Dry CF method and the AOAC Official Method 966.24 results. For the accuracy claim (n = 75), a correlation factor of r2 = 0.91 (coliform) could be assigned, as stated in the application for Performance-Tested Method. No significant variations in coliform bacterial counts were observed with different production lots or plates of diverse storage age by the quality consistency and storage robustness studies.

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 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)0.002
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 score0.091
Threshold uncertainty score0.327

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.026
GPT teacher head0.355
Teacher spread0.330 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations8
Published2006
Admission routes1
Has abstractyes

Explore more

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