MétaCan
Menu
← Back to cohort
Record W3092784404 · doi:10.1007/s11356-020-11236-7

Ecotoxicology, revisiting its pioneers.

2021· preprint· en· W3092784404 on OpenAlexaff
Paule Vasseur, Jean‐François Masfaraud, C. Blaise

Bibliographic record

VenuePubMed · 2021
Typepreprint
Languageen
FieldEnvironmental Science
TopicToxic Organic Pollutants Impact
Canadian institutionsEnvironment and Climate Change Canada
Fundersnot available
KeywordsEcotoxicologyComputer scienceChemistryEnvironmental chemistry

Abstract

fetched live from OpenAlex

Ecotoxicology is a discipline resulting from pollution events that harmed human and environmental health by the mid-twentieth century. Environmental considerations were simply inexistent at this time, and inevitably deleterious effects and environmental disasters followed. These historical events, like Clear Lake disaster in California, will be recalled, as well as new concepts developed, and scientists involved in these findings. A special tribute is given to Professor Jean-Michel Jouany who conceptualized newly acquired knowledge into an emerging discipline, which he named "ecotoxicology" in the 1960s, and understood to be "toxicology in an ecological perspective." However, René Truhaut is considered as the "father of ecotoxicology" by posterity, while his young mentor Jouany was shadowed by the latter. It is timely to "open the book" as concerns these two exceptional personalities and their working relationships, first to set the record straight and second to give credit where credit is due.

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)0.005
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.019
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.007
Science and technology studies0.0010.004
Scholarly communication0.0050.009
Open science0.0010.003
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0190.018

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 head0.025
GPT teacher head0.232
Teacher spread0.207 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations1
Published2021
Admission routes1
Has abstractyes

Explore more

Same venuePubMed→Same topicToxic Organic Pollutants Impact→French-language works237,207→