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Record W2167128887 · doi:10.1002/etc.5620190718

Growth of fathead minnows in oilsand-processed wastewater in laboratory and field

2000· article· en· W2167128887 on OpenAlexaffabout
Paula Siwik, T. Van Meer, Michael D. MacKinnon, Cynthia A. Paszkowski

Bibliographic record

VenueEnvironmental Toxicology and Chemistry · 2000
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAquaculture Nutrition and Growth
Canadian institutionsSyncrude (Canada)University of Alberta
Fundersnot available
KeywordsEnvironmental scienceWastewaterEnvironmental chemistryBiologyChemistryEnvironmental engineering

Abstract

fetched live from OpenAlex

Abstract Two waste products of Syncrude Canada Ltd. (SCL) oilsands mine are mature fine tailings (MFT), a toxic aqueous suspension of particles, organic acids, bitumen, and metals, and tailings pond water (TPW), a saline solution containing organic and inorganic contaminants. The chemical profiles of MFT interstitial water and TPW are very similar. Syncrude Canada has proposed disposing of MFT in constructed lakes, which would be lined with MFT and capped with clean water. As the MFT consolidates, MFT-associated water would be released into the overlying watercap. Prototype ponds support fathead minnows (Pimephales promelas), but the long-term viability of these populations is unknown. This study attempts to determine if exposure to MFT and TPW, a related waste product, affected growth of fathead minnow larvae in the laboratory and field. Laboratory larval growth bioassays (7 and 56 d) on whole effluent from numerous prototype ponds yielded no significant differences in dry weight, but one 7-d bioassay showed reduced survival in two SCL sites. A 56-d growth bioassay showed significant increases in length of fish exposed to SCL wastewater at 7 d but not at 28 or 56 d. Larvae exposed as embryos and then introduced into field mesocosms did display significant differences in dry weight. In this instance, fish exposed to wastewater were significantly larger during the laboratory portion of the test (initial), but after 21 d in a field mesocosm (final), they were similar in size or smaller than fish growing in nonprocessed water.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.004
GPT teacher head0.178
Teacher spread0.174 · 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

Citations63
Published2000
Admission routes2
Has abstractyes

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