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Record W2015495938 · doi:10.1002/etc.5620191012

Influence of salinity on<i>Vibrio fischeri</i>and<i>lux</i>-modified<i>Pseudomonas fluorescens</i>toxicity bioassays

2000· article· en· W2015495938 on OpenAlexaff
Sonja V. Cook, Angus Chu, Ron H Goodman

Bibliographic record

VenueEnvironmental Toxicology and Chemistry · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Toxicology and Ecotoxicology
Canadian institutionsImperial Oil (Canada)University of Calgary
Fundersnot available
KeywordsPseudomonas fluorescensBioassayVibrioSalinityBiologyMicrobiologyMarine bacteriophageBacteriaPseudomonasVibrionaceaeEnvironmental chemistryFood scienceChemistryEcology

Abstract

fetched live from OpenAlex

Abstract This study compares the toxicological response of the marine bacteria Vibrio fischeri and a lux-modified soil and freshwater bacteria, Pseudomonas fluorescens, to saline contamination alone and in the presence of chromium and phenol. Saline solutions are more toxic to P. fluorescens than V. fischeri, and salinity can stimulate luminescence in V. fischeri. Vibrio fischeri is about 10 times more sensitive than P. fluorescens to chromium and phenol. However, the response of P. fluorescens to these toxicants is sensitive to changes in saline contamination, while the response of V. fischeri is not. Therefore, the P. fluorescens bioassay may be a more appropriate bioassay organism than V. fischeri when evaluating the toxicological impact of salinity within saline environmental samples.

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 score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
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)0.0010.000

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 head0.005
GPT teacher head0.198
Teacher spread0.193 · 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

Citations35
Published2000
Admission routes1
Has abstractyes

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