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Record W2056222624 · doi:10.1038/sj.jim.7000006

Phenol metabolism by two microorganisms isolated from Amazonian forest soil samples

2000· article· en· W2056222624 on OpenAlexaff
Artur Eduardo Ribeiro Bastos, Valdemar Luiz Tornisielo, Shunsuke Nozawa, J. T. Trevors, Antônio Rossi

Bibliographic record

VenueJournal of Industrial Microbiology & Biotechnology · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicMicrobial bioremediation and biosurfactants
Canadian institutionsUniversity of Guelph
FundersFundação de Amparo à Pesquisa do Estado de São Paulo
KeywordsMicroorganismPhenolCatecholAlcaligenes faecalisChemistryAlcaligenesMetabolitePhenolsBiochemistryMineralization (soil science)EnzymeMicrobiologyMetabolismExtracellularBiologyBacteriaOrganic chemistryPseudomonas

Abstract

fetched live from OpenAlex

Two microorganisms isolated from Amazonian forest soil samples and identified as Candida tropicalis and Alcaligenes faecalis were capable of degrading phenol (16 and 12 mM, respectively) at high salt concentrations (15% and 5.6%, respectively). Chromatographic and enzymatic studies revealed that each microorganism cleaved phenol at the ortho position with total phenol mineralization. 14C-phenol mineralization assays showed that both microorganisms assimilated about 30% of the total label. No phenol degradation metabolite (i.e., catechol, cis, cis-muconic acid) was detected in the intercellular medium. The presence of phenol hydroxylase (EC 1.14.13.7) and catechol 1,2-dioxygenase (EC 1.13.11.1) extracellular activity suggested that these microorganisms may secrete these enzymes into the extracellular medium. Journal of Industrial Microbiology & Biotechnology (2000) 24, 403–409.

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)0.000
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 score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.011
GPT teacher head0.201
Teacher spread0.191 · 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

Citations31
Published2000
Admission routes1
Has abstractyes

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