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Record W2152802777 · doi:10.1007/s10295-002-0017-x

Identification of bacteria contaminating pulp and a paper machine in a Canadian paper mill

2003· article· en· W2152802777 on OpenAlexaffabout
Elyse Desjardins, Carole Beaulieu

Bibliographic record

VenueJournal of Industrial Microbiology & Biotechnology · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicMicrobial Community Ecology and Physiology
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsBiologyPulp (tooth)16S ribosomal RNABacteriaPulp millPseudomonasMicrobiologyWaste managementEngineeringGenetics

Abstract

fetched live from OpenAlex

Over 100 bacteria from pulp and slime samples in a Canadian paper mill were identified by partial sequencing of their 16S rDNAs. Seventy-one percent of the isolates could be assigned to a bacterial genus with a high level of confidence. Another 12% exhibited at least 95% similarity within their 16S rDNA sequence with unidentified organisms that originate from warm or wet environments. Pseudomonas, Bacillus, and Pseudoxanthomonas isolates were represented at a relatively high proportion in both pulp and slime samples. This is the first time that Pseudoxanthomonas strains have been isolated from pulp and slime samples on a paper machine.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.704
Threshold uncertainty score0.596

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0040.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.010
GPT teacher head0.209
Teacher spread0.200 · 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 designObservational
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

Citations37
Published2003
Admission routes2
Has abstractyes

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