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Record W2033518409 · doi:10.1021/es800051z

Real-Time PCR Detection and Quantification of Nine Potential Sources of Fecal Contamination by Analysis of Mitochondrial Cytochrome <i>b</i> Targets

2008· article· en· W2033518409 on OpenAlexaboutno aff
William B. Schill, M.V. Mathes

Bibliographic record

VenueEnvironmental Science & Technology · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMolecular Biology Techniques and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsFecesMitochondrial DNABiologyCytochrome bPrimer (cosmetics)Human fecesContaminationVeterinary medicineSewageAnimal scienceMolecular biologyChemistryEcologyGeneticsEnvironmental scienceGene

Abstract

fetched live from OpenAlex

We designed and tested real-time PCR probe/primer sets to detect and quantify Cytochrome b sequences of mitochondrial DNA (mtDNA) from nine vertebrate species of pet (dog), farm (cow, chicken, sheep, horse, pig), wildlife (Canada goose, white-tailed deer), and human. Linear ranges of the assays were from 10(1) to 10(8) copies/microl. To formally test the performance of the assays, twenty blinded fecal suspension samples were analyzed by real-time PCR to identify the source of the feces. Sixteen of the twenty samples were correctly and unambiguously identified. Average sensitivity was calculated to be 0.850, while average specificity was found to be 0.994. One beef cow sample was not detected, but mtDNA from 11 other beef cattle of both sexes and varying physiological states was found in concentrations similar (3.45 x 10(7) copies/g) to thatfound in human feces (1.1 x 10(7) copies/g). Thus, environmental conditions and sample handling are probably important factors for successful detection of fecal mtDNA. When sewage samples were analyzed, only human mtDNA (7.2 x 10(4) copies/ 100 mL) was detected. With a detection threshold of 250 copies/reaction, an efficient concentration and purification method resulted in a final detection limit for human feces of 1.8 mg/ 100 mL water.

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)0.000
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 score0.026
Threshold uncertainty score0.746

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
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 head0.003
GPT teacher head0.208
Teacher spread0.205 · 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

Citations70
Published2008
Admission routes1
Has abstractyes

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