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Record W2130895821 · doi:10.1002/etc.2963

Toxicity of fluoride to aquatic species and evaluation of toxicity modifying factors

2015· article· en· W2130895821 on OpenAlex

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

VenueEnvironmental Toxicology and Chemistry · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Quality and Pollution Assessment
Canadian institutionsCameco (Canada)Nautilus Environmental
FundersCameco
KeywordsHyalella aztecaCeriodaphnia dubiaToxicityRainbow troutChronic toxicityAcute toxicityBiologyEnvironmental chemistryToxicologyEcotoxicologyAquatic toxicologyChemistryEcologyFisheryAmphipodaFish <Actinopterygii>Crustacean

Abstract

fetched live from OpenAlex

The present study was performed to investigate the toxicity of fluoride to a variety of freshwater aquatic organisms and to establish whether water quality variables contribute substantively to modifying its toxicity. Water hardness, chloride, and alkalinity were tested as possible toxicity modifying factors for fluoride using acute toxicity tests with Hyalella azteca and Oncorhynchus mykiss. Chloride appeared to be the major toxicity modifying factor for fluoride in these acute toxicity tests. The chronic toxicity of fluoride was evaluated with a variety of species, including 3 fish (Pimephales promelas, O. mykiss, and Salvelinus namaycush), 3 invertebrates (Ceriodaphnia dubia, H. azteca, and Chironomus dilutus), 1 plant (Lemna minor), and 1 alga (Pseudokirchneriella subcapitata). Hyalella azteca was the most sensitive species overall, and O. mykiss was the most sensitive species of fish. The role of chloride as a toxicity modifying factor was inconsistent between species in the chronic toxicity tests.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.051
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0010.000

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 head0.062
GPT teacher head0.288
Teacher spread0.226 · 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