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Record W2107932219 · doi:10.1139/w99-129

Molecular analysis and development of 16S rRNA oligonucleotide probes to characterize a diclofop-methyl-degrading biofilm consortium

2000· article· en· W2107932219 on OpenAlexaffvenue
Louise Laramée, John R. Lawrence, Charles W. Greer

Bibliographic record

VenueCanadian Journal of Microbiology · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicMicrobial bioremediation and biosurfactants
Canadian institutionsNational Research Council CanadaMcGill University
Fundersnot available
KeywordsBiologyBacteriaOligonucleotideBiofilmGene16S ribosomal RNACatabolismgenomic DNAMicrobiologyDNARibosomal RNAMolecular biologyBiochemistryGeneticsEnzyme

Abstract

fetched live from OpenAlex

Genomic DNA from nine individual bacteria, isolated from a diclofop-methyl-degrading biofilm consortium, was extracted for genetic characterization. The degradation of diclofop-methyl produces metabolites that are known intermediates or substrates for bacteria that degrade a variety of chlorinated aromatic compounds. Accordingly, oligonucleotide primers were designed from specific catabolic genes for chlorinated organic degradation pathways, and tested by PCR to determine if these genes are involved in diclofop-methyl degradation. DNA homology between the PCR products and the known catabolic genes investigated by Southern hybridization analysis and by sequencing, suggested that novel catabolic genes are functioning in the isolates. Specific fluorescent oligonucleotides were designed for two of the isolates, following 16S rDNA sequencing and identification of each of the isolates. These probes were successfully used for fluorescent in situ hybridization (FISH) studies of the two isolates in the biofilm consortium.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.199
Teacher spread0.189 · 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 source (direct Gemma or distilled Codex), 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

Citations28
Published2000
Admission routes2
Has abstractyes

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Same venueCanadian Journal of MicrobiologySame topicMicrobial bioremediation and biosurfactantsFrench-language works237,207