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Record W2155871067 · doi:10.2166/wqrj.2004.016

Summary of Case Studies Investigating the Causes of Pulp and Paper Mill Effluent Regulatory Toxicity

2004· article· en· W2155871067 on OpenAlexfundaboutno aff
Tibor Kovács, Sharon Gibbons, Brian O’Connor, P. Martel, Michael G. Paice, Valerie Naish, R.H. Voss

Bibliographic record

VenueWater Quality Research Journal · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Toxicology and Ecotoxicology
Canadian institutionsnot available
FundersNewfoundland and Labrador
KeywordsDaphnia magnaRainbow troutEffluentToxicantToxicityDaphniaPaper millAcute toxicityTroutBiologyToxicologyCladoceraPollutantPulp millEnvironmental chemistryFisheryPulp and paper industryChemistryEcologyEnvironmental scienceEnvironmental engineeringFish <Actinopterygii>CrustaceanEngineering

Abstract

fetched live from OpenAlex

Abstract In Canada, effluents from pulp and paper mills are regulated for toxicity. The regulation requires ≥50% survival of rainbow trout (Oncorhynchus mykiss) exposed to full-strength (i.e., 100%) effluent for 96 h in tests that must be conducted monthly. The regulation also calls for ≥50% survival of Daphnia magna exposed to 100% effluent for 48 h in weekly monitoring tests. Every year, about 10 to 25% of the mills exceed the regulatory limit at least once in tests with either rainbow trout or Daphnia magna. Between 1996 and 2003, we investigated 84 such cases from 32 mills. Of the 84 investigations, 49 involved only trout, 29 involved only Daphnia, and six involved both species. We identified the actual cause of toxicity in 70% of the cases and partially or tentatively identified the toxicant(s) in 17% more. In the cases involving only trout, the most frequent causes of toxicity were related to biotreatment performance (e.g., ammonia). In the cases involving only Daphnia, the most frequent cause of toxicity seemed to be related to polymeric formulations. For those cases involving both trout and Daphnia, the cause of toxicity was traced to more than one compound or to excess concentrations of a specific compound resulting from a spill or biotreatment-related problems.

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)0.004
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0080.005
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.131
GPT teacher head0.393
Teacher spread0.261 · 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 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

Citations11
Published2004
Admission routes2
Has abstractyes

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