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Record W2069029552 · doi:10.3325/cmj.2010.51.306

Review of Detection of Brucella sp. by Polymerase Chain Reaction

2010· review· en· W2069029552 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

VenueCroatian Medical Journal · 2010
Typereview
Languageen
FieldVeterinary
TopicBrucella: diagnosis, epidemiology, treatment
Canadian institutionsCanadian Food Inspection Agency
Fundersnot available
KeywordsBrucellaPolymerase chain reactionMultiplex polymerase chain reactionBrucellosisBiovarBiologyTypingIdentification (biology)MicrobiologyComputational biologyVirologyBacteriaGeneticsGene

Abstract

fetched live from OpenAlex

Here we present a review of most of the currently used polymerase chain reaction (PCR)-based methods for identification of Brucella bacteria in biological samples. We focused in particular on methods using single-pair primers, multiplex primers, real-time PCRs, PCRs for marine Brucella, and PCRs for molecular biotyping. These methods are becoming very important tools for the identification of Brucella, at the species level and recently also at the biovar level. These techniques require minimum biological containment and can provide results in a very short time. In addition, genetic fingerprinting of isolates aid in epidemiological studies of the disease and its control. PCR-based methods are more useful and practical than conventional methods used to identify Brucella spp., and new methods for Brucella spp. identification and typing are still being developed. However, the sensitivity, specificity, and issues of quality control and quality assurance using these methods must be fully validated on clinical samples before PCR can be used in routine laboratory testing for brucellosis.

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)0.005
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.932
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.072
GPT teacher head0.399
Teacher spread0.328 · 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