MétaCan
Menu
Back to cohort
Record W2912215896 · doi:10.1002/aws2.1121

State approaches to addressing cyanotoxins in drinking water

2019· article· en· W2912215896 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueAWWA Water Science · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Ecosystems and Phytoplankton Dynamics
Canadian institutionsnot available
FundersGovernment of CanadaPublic Health Agency of CanadaWater Environment and Reuse FoundationAmerican Water Works Association Research FoundationWater Research FoundationPennsylvania Department of Environmental ProtectionU.S. Environmental Protection AgencyNational Aeronautics and Space Administration
KeywordsCylindrospermopsinEnvironmental healthJurisdictionClean Water ActAgency (philosophy)Environmental planningEnvironmental scienceEnvironmental protectionScope (computer science)CyanotoxinEnvironmental resource managementWater qualityPolitical scienceMicrocystinEcologyLawBiologyMedicineCyanobacteria

Abstract

fetched live from OpenAlex

Cyanobacterial blooms present a risk to water supplies, especially in nutrient‐enriched bodies of water. Some algal blooms can produce cyanotoxins at levels of concern for human health and aquatic ecosystems. Currently no federally enforceable limits exist for microcystins, cylindrospermopsin, or any other cyanotoxins. However, several states have taken action based on nonenforceable U.S. Environmental Protection Agency's (USEPA's) health advisories and their own processes. This study assessed the status and scope of those state‐level programs. Data were collected through interviews with state regulatory officials accompanied by publicly available information. The authors contacted officials in each of the 50 U.S. states. Forty‐six provided responses, and four have only publicly available information. Twenty‐nine states reported to have already developed or are currently developing guidance, while 13 indicated that cyanotoxins are not an issue of concern within their jurisdiction. Two states appear in both categories. The statuses of the remaining 10 states' programs fall in between.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.396
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.004

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 head0.046
GPT teacher head0.223
Teacher spread0.177 · 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