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The use of multiplex PCR reactions to characterize populations of lactic acid bacteria associated with meat spoilage

2000· article· en· W2058666119 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

VenueLetters in Applied Microbiology · 2000
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicProbiotics and Fermented Foods
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsLactobacillus sakeiLeuconostocLactic acidBacteriaBiologyMultiplex polymerase chain reaction16S ribosomal RNAPolymerase chain reactionFood scienceLactobacillusFood spoilageMicrobiologyBiochemistryGeneticsGene

Abstract

fetched live from OpenAlex

A rapid, systematic and reliable approach for identifying lactic acid bacteria associated with meat was developed, allowing for detection of Carnobacterium spp., Lactobacillus curvatus, Lact. sakei and Leuconostoc spp. Polymerase chain reaction primers specific for Carnobacterium and Leuconostoc were created from 16S rRNA oligonucleotide probes and used in combination with species-specific primers for the 16S/23S rRNA spacer region of Lact. curvatus and Lact. sakei in multiplex PCR reactions. The method was used successfully to characterize lactic acid bacteria isolated from a vacuum-packaged pork loin stored at 2 degrees C. Seventy isolates were selected for identification and 52 were determined to be Lact. sakei, while the remaining 18 isolates were identified as Leuconostoc spp.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.746
Threshold uncertainty score0.191

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 head0.041
GPT teacher head0.210
Teacher spread0.169 · 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