MétaCan
Menu
Back to cohort
Record W2757555406 · doi:10.2166/wqrj.2017.019

Development of an in-stream environmental exposure model for assessing down-the-drain chemicals in Southern Ontario

2017· article· en· W2757555406 on OpenAlexaboutno aff
Darci Ferrer, Paul C. DeLeo

Bibliographic record

VenueWater Quality Research Journal · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicPharmaceutical and Antibiotic Environmental Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental scienceTriclosanSurface waterHydrology (agriculture)Flow (mathematics)Environmental engineeringGeologyMathematics

Abstract

fetched live from OpenAlex

Abstract In order to address increased interest from scientists and regulators in quantifying environmental risks associated with release of common down-the-drain consumer products, a single-medium contaminant fate model for the lower St. Lawrence drainage basin in Southern Ontario was developed. The model was built within the pre-existing framework of the iSTREEM® in-stream environmental exposure model, which previously only contained US geographies. Data for the model were obtained from Canadian Government sources. In order to assess the model's strengths and limitations, concentrations of the chemicals triclosan and carbamazepine in surface water were compared to the predicted environmental concentrations (PECs) generated by the model for both mean and low flow scenarios. Results of the PECs and the measured surface water concentrations were comparable, with the surface water concentrations generally falling in between the mean and low flow PECs on a cumulative distribution curve.

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 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)0.006
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.354
Threshold uncertainty score0.659

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.230
GPT teacher head0.440
Teacher spread0.210 · 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 teacher head, 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

Citations21
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueWater Quality Research JournalSame topicPharmaceutical and Antibiotic Environmental ImpactsFrench-language works237,207