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Record W2802731048 · doi:10.1002/awwa.1044

Hexavalent Chromium in Drinking Water

2018· article· en· W2802731048 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAmerican Water Works Association · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicChromium effects and bioremediation
Canadian institutionsHealth Canada
Fundersnot available
KeywordsHexavalent chromiumChromiumRisk assessmentWater contaminationToxicologyContaminationToxicityEnvironmental scienceEnvironmental chemistryEnvironmental healthChemistryBiologyMedicineEcologyComputer science

Abstract

fetched live from OpenAlex

The risk assessment of chromium in drinking water is complex. To better understand this complexity, the essential information on exposure, analytical and treatment methods, toxicology, and mode of action (MOA) on which agencies based their risk assessments are provided. Humans are exposed to an average of 0.2–2 μg hexavalent chromium per liter in drinking water through natural erosion of soil and rocks or by contamination from industrial sources. Internationally, drinking water limits for total chromium range from 50 to 100 μg/L. These values are based on intestinal toxicity data from experimental animals, since human toxicity data via the oral route are lacking. MOA analysis supports a progression from noncancer to cancer effects via a nonmutagenic MOA and therefore a threshold approach is appropriate for the risk assessment of chromium in drinking water. Drinking water limits derived from this approach are measureable by available analytical methods and achievable by available treatment technologies, and are protective of both cancer and noncancer effects.

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 categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score1.000

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.002

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 head0.003
GPT teacher head0.204
Teacher spread0.201 · 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