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Metalworking fluids biodiversity characterization

2009· article· en· W2029412982 on OpenAlex
Marc Veillette, Caroline Duchaine

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".

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Applied Microbiology · 2009
Typearticle
Languageen
FieldMedicine
TopicOccupational exposure and asthma
Canadian institutionsInstitut universitaire de cardiologie et de pneumologie de QuébecUniversité Laval
FundersInstitute of Circulatory and Respiratory HealthCanadian Institutes of Health ResearchInstitut de Recherche Robert-Sauvé en Santé et en Sécurité du Travail
KeywordsMetalworkingBiodiversityBiologyBusinessEcologyGeographyArchaeology

Abstract

fetched live from OpenAlex

AIMS: Hypersensitivity pneumonitis of machinists associated with metalworking fluids (MWF) was recently linked to Mycobacterium immunogenum. In addition to Mycobacterium, impacts of continuous and massive contact to other micro-organisms, such as Pseudomonas, were little studied. This report intended to quantify and characterize the microbial load of 44 in-use MWF. METHODS AND RESULTS: The main biodiversity of MWF was assessed using cultural methods, quantitative PCR (qPCR) and denaturing gradient gel electrophoresis (DGGE). Total bacteria concentrations ranged from undetectable to 10(9) 16S rRNA gene copies per millilitre. Concentrations obtained by qPCR were up to five orders of magnitude higher than by culture, suggesting that MWF contamination is generally underestimated. Two samples showed high concentrations of Myco. immunogenum (1.55 x 10(7) and 3.49 x 10(5) 16S rRNA gene copies per millilitre). The overall biodiversity was low, as observed by culture and DGGE, and was comparable to data found in the literature. Pseudomonas pseudoalcaligenes was by far the main bacteria found in MWF samples (33 out of 44), followed by Ochrobactrum anthropi (32 out of 44). There was no significant relationship between the biodiversity profiles and the kind of MWF or equipment used, making it difficult to predict which micro-organisms will colonize each particular MWF. CONCLUSIONS: Very high concentrations of bacteria were found in most MWF studied and limited biodiversities were observed. Many species of micro-organisms were retrieved from MWF samples, but they were mostly colonized by Pseudomonas pseudoalcaligenes and Ochrobactrum anthropi. SIGNIFICANCE AND IMPACT OF THE STUDY: The major micro-organisms observed or recovered in this study from in-use MWF were present in very high concentrations, and thus further studies are needed to confirm their role in workers' respiratory disorders or health-related problems.

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 score0.431
Threshold uncertainty score0.222

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 head0.010
GPT teacher head0.228
Teacher spread0.218 · 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