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Intralaboratory experience with a battery of bioassays: Colombia experience

2000· article· en· W2081579181 on OpenAlexaboutno aff
M. C. Díaz-Báez, Joel Pérez

Bibliographic record

VenueEnvironmental Toxicology · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Toxicology and Ecotoxicology
Canadian institutionsnot available
Fundersnot available
KeywordsBioassayToxicantPesticideToxicologyCadmiumEnvironmental chemistryMetolachlorEcotoxicologyEnvironmental scienceBiologyAnimal scienceChemistryEcologyToxicityAtrazine

Abstract

fetched live from OpenAlex

A joint effort to evaluate a battery of bioassays for regulatory purposes was conducted as an intercalibration exercise by institutions in eight countries (Argentina, Canada, Chile, Colombia, Costa Rica, India, Mexico, and Ukraine) with support from the International Development Research Centre (IDRC). The precision of the tests carried out in the Colombian Laboratory was evaluated by comparing the results obtained with the reference toxicants used as positive controls, as well as with a set of five blind samples which in fact had the same toxicant concentration (metolachlor plus cadmium). The coefficients of variation (CV) obtained with each bioassay for the positive controls ranged from 5 to 21% except for the Panagrellus test which gave CVs as high as 67%. The 100% sample concentration results of the mixture (metolachlor/cadmium) showed CVs between 2 and 55%. The highest value was again obtained with Panagrellus and the lowest value with the root elongation test. Even though the Panagrellus test had previously been used in our laboratory, its extra requirements in terms of time and training could be the reason for the high variability. The results also showed that the most sensitive test for heavy metals and pesticides was the Daphnia test. Hydra and Panagrellus tests showed the highest sensitivity response for the organics evaluated. © 2000 John Wiley & Sons, Inc. Environ Toxicol 15: 297–303, 2000

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 categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.173
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.004
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.1750.002

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 head0.200
Teacher spread0.195 · 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; both teacher heads agree on what is shown here.

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

Citations5
Published2000
Admission routes1
Has abstractyes

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