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Record W2921583624 · doi:10.1002/etc.4408

Response of a Small Mammal Population Postremediation for an Accidental Bitumen and Steam Release from a Wellhead in the Athabasca Oil Sands

2019· article· en· W2921583624 on OpenAlexaff
Judit E. G. Smits, Greg Sanders, Michael Charlebois

Bibliographic record

VenueEnvironmental Toxicology and Chemistry · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicToxic Organic Pollutants Impact
Canadian institutionsCalgary Laboratory ServicesUniversity of Calgary
Fundersnot available
KeywordsOil sandsWellheadPopulationEnvironmental chemistryAsphaltEnvironmental scienceBioindicatorDetoxification (alternative medicine)ChemistryGeologyPetroleum engineeringGeography

Abstract

fetched live from OpenAlex

Two releases from steam assisted gravity drainage (SAGD) wellheads occurred 3 yr apart. To track recovery of the affected areas, red-backed voles were studied 1 and 4 yr later, using population estimates, hepatic detoxification effort, body condition, and tissue metal levels as bioindicators of site recovery. From years 1 to 4, higher ethoxyresorufin-O-deethylase induction was no longer evident, capture rate was lower, and body lead residues were no longer (inversely) correlated with body condition. Environ Toxicol Chem 2019;38:1542-1548. © 2019 SETAC.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.993
Threshold uncertainty score0.014

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 head0.007
GPT teacher head0.214
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 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

Citations1
Published2019
Admission routes1
Has abstractyes

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