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Record W4405099239 · doi:10.22215/etd/2024-16333

In vitro bioassays to estimate avian toxicity and contaminant levels in passive sampler extracts from wetlands surrounding tailings ponds in the Athabasca Oil Sands Region

2024· dissertation· en· W4405099239 on OpenAlexaffabout
Laura Christine Van Raalte

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsCarleton University
Fundersnot available
KeywordsTailingsOil sandsWetlandEnvironmental scienceExtraction (chemistry)Environmental chemistryBioassayToxicityEcosystemPeatMining engineeringEcologyGeologyChemistryBiologyAsphaltGeography

Abstract

fetched live from OpenAlex

Oil extraction in the Athabasca Oil Sands Region generates large volumes of waste, called tailings, that are stored in tailings ponds.These tailings are toxic largely due to the presence of naphthenic acids (NAs) and concern is mounting about seepage into the surrounding tributaries.The objective of this thesis was to rank the relative toxicity of passive sampler extracts from 6 wetlands using in vitro screening, determine if bioactivity could predict NA concentrations, and elucidate species differences between chickens and double-crested cormorants (DCCO).Hepatic cells were cultured as 3D spheroids.Higher levels of NAs were found in wetlands close to oil sands activity compared to ones further away.The concentrations of NAs were reflected in the bioactivity results for chickens which were also determined to be more sensitive than DCCO.This thesis demonstrates the use of a non-animal screening method for environmental monitoring in an ecosystem of concern in Canada.Beck, E. M.,

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.979
Threshold uncertainty score0.041

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 head0.018
GPT teacher head0.276
Teacher spread0.258 · 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 designBench or experimental
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

Citations0
Published2024
Admission routes2
Has abstractyes

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