MétaCan
Menu
Back to cohort
Record W7038159997

Great Lakes Initiative: EPA and States Have Made Progress, but Much Remains to Be Done If Water Quality Goals Are to Be Achieved

2008· article· en· W7038159997 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of North Texas Digital Library (University of North Texas) · 2008
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicDrug Solubulity and Delivery Systems
Canadian institutionsnot available
Fundersnot available
KeywordsWater qualityClean Water ActPollutantAgency (philosophy)LegislationGovernment (linguistics)Environmental qualityQuality (philosophy)
DOInot available

Abstract

fetched live from OpenAlex

Testimony issued by the Government Accountability Office with an abstract that begins "Millions of people in the United States and Canada depend on the Great Lakes for drinking water, recreation, and economic livelihood. During the 1970s, it became apparent that pollutants discharged into the Great Lakes Basin from point sources, such as industrial and municipal facilities, or from nonpoint sources, such as air emissions from power plants, were harming the Great Lakes. Some of these pollutants, known as bioaccumulative chemicals of concern (BCC), pose risks to fish and other species as well as to the humans and wildlife that consume them. In 1995, the Environmental Protection Agency (EPA) issued the Great Lakes Initiative (GLI). The GLI established water quality criteria to be used by states to establish pollutant discharge limits for some BCCs and other pollutants that are discharged by point sources. The GLI also allows states to include flexible permit implementation procedures (flexibilities) that allow facilities' discharges to exceed GLI criteria. This testimony is based on GAO's July 2005 report, Great Lakes Initiative: EPA Needs to Better Ensure the Complete and Consistent Implementation of Water Quality Standards (GAO-05-829) and updated information from EPA and the Great Lakes states. This statement addresses (1) the status of EPA's efforts to develop and approve methods to measure pollutants at the GLI water quality criteria levels, (2) the use of permit flexibilities, and (3) EPA's actions to implement GAO's 2005 recommendations."

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.143
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.003
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 head0.074
GPT teacher head0.288
Teacher spread0.214 · 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.

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
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueUniversity of North Texas Digital Library (University of North Texas)Same topicDrug Solubulity and Delivery SystemsFrench-language works237,207