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Record W7051495629

Ontario's water quality objective development process

2019· report· en· W7051495629 on OpenAlexaboutno aff

Bibliographic record

VenueThe Atrium (University of Guelph) · 2019
Typereport
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
Fundersnot available
KeywordsWater qualityChristian ministryProcess (computing)Aquatic ecosystemQuality (philosophy)Aquatic environment
DOInot available

Abstract

fetched live from OpenAlex

As part of its program to ensure that the surface waters of Ontario are satisfactory for aquatic life and recreation, the Ontario Ministry of the Environment develops Provincial Water Quality Objectives (PWQOs) and Guidelines (PWQGs). This report details the procedures used to develop PWQOs and PWQGs. PWQOs are developed from the best available knowledge on the effects of substances on aquatic life. Data are required for acute and chronic toxicity, bioaccumulation and mutagenicity. Also considered is available information on environmental fate, physical-chemical properties, taste and odour in water and tainting of fish tissues. If adequate information is unavailable for setting a PWQO, a PWQG is developed using uncertainty factors which depend on the quantity and quality of the toxicological data.

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)0.017
metaresearch head score (Gemma)0.017
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: none
Teacher disagreement score0.067
Threshold uncertainty score0.363

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.017
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0080.007
Science and technology studies0.0050.001
Scholarly communication0.0060.001
Open science0.0030.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0310.012

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 head0.032
GPT teacher head0.274
Teacher spread0.242 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

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