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Record W37674406 · doi:10.1039/d3em00202k

Institute on Aging’s new Senior Campus opens; community event this Saturday

2011· article· en· W37674406 on OpenAlexfundaboutno aff
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Bibliographic record

VenueEnvironmental Science Processes & Impacts · 2011
Typearticle
Languageen
FieldPsychology
TopicHealth and Well-being Studies
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of CanadaNatural Sciences and Engineering Research Council of Canada
KeywordsEvent (particle physics)GerontologyMedicine

Abstract

fetched live from OpenAlex

Perfluorooctanoic acid (PFOA) and perfluorooctane sulfonic acid (PFOS) are two of the most commonly researched per- and polyfluoroalkyl substances (PFAS). Globally, many long-chain PFAS compounds including PFOS and PFOA are highly regulated and, in some countries, PFAS use in commercial products is strictly prohibited. Despite the legal regulation of these 'forever chemicals' under the Canadian Environmental Protection Act, PFOA and PFOS compounds are still found in high concentrations in discharges from wastewater treatment plants, both from liquid and sludge streams. Yet, their potential impact on wastewater treatment effectiveness remains poorly understood. The findings of this research show that: (1) PFOS and PFOA might be hindering the overall outcome treatment performance - calling into question the efficacy of Canada's existing wastewater treatment regulatory standard (Wastewater Systems Effluent Regulations, SOR/2012-139), and (2) specific microorganisms from the <i>Thiobacillus</i> and <i>Pseudomonas</i> genera seem capable of adsorbing PFOS and PFOA onto their cell wall and even degrading the chemicals, but it is unclear as to what extent degradation occurs. The results also raise questions whether existing wastewater regulations should be expanded to include the detection and monitoring of PFAS, as well as the establishment of a regulatory wastewater treatment plant discharge standard for PFAS that is protective of human and ecological health.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.690
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 studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.046
GPT teacher head0.342
Teacher spread0.296 · 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; both teacher heads agree on what is shown here.

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
Published2011
Admission routes2
Has abstractyes

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