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Record W2989754157 · doi:10.1289/isee.2011.00384

SURVEILLANCE OF POTENTIAL ENVIRONMENTAL EXPOSURE TO GOLF TURF PESTICIDES

2011· article· en· W2989754157 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueISEE Conference Abstracts · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicTurfgrass Adaptation and Management
Canadian institutionsOccupational Cancer Research CentreUniversity of British Columbia
Fundersnot available
KeywordsChlorothalonilEnvironmental sciencePesticideInternational agencyGeographyEcology

Abstract

fetched live from OpenAlex

Background and Aims: In Canada, golf courses are often permitted continued use of pesticides banned for cosmetic purposes, including those classified as “possible” carcinogens by the International Agency for Research on Cancer (IARC). As part of a National Carcinogen Surveillance Project (CAREX Canada), we geographically estimate environmental exposure potential for “possibly” carcinogenic pesticides applied to golf turf in Canadian watersheds. Methods: Pesticide type, application frequency, and course size were obtained from Canadian Golf Superintendents’ Association surveys (2004, 2008). Estimated annual use (kilograms active ingredient) were calculated using product label application rates from the Pest Management Regulatory Agency. A Canadian golf course database was compiled in a geographic information system (GIS) from national landuse, business directories and online sources. GoogleEarth was used to verify locations and rank courses by relative surrounding housing density (n): Low 0-2; Low-Medium 2-10; Medium-High 10-20; High >20. A method to develop an average course perimeter polygon for estimating adjacent populations is being developed. Results: Data sources of course locations were frequently inadequate. Locations were corrected to more accurately assess adjacent housing density. We identified three IARC “possible” carcinogens being used: 2,4-D, MCPP and chlorothalonil. Average annual use was calculated for a typical course and multiplied by number of courses in each watershed. For example, an average course applies 158 kg chlorothalonil annually. We identify hotspot watersheds, such as that in Western Canada using up to 19,586 kg (lower Fraser Valley). Percentage of courses with highest surrounding housing density varies by province: 11.8% British Columbia, 8.6% Alberta, and 1.4% Saskatchewan. Exposure surveillance information is disseminated in map format for comparison within and across provinces. Conclusions: We geographically assess golf course pesticide use across Canada at the watershed level to identify areas with greatest potential for environmental exposures. Ongoing research will provide more detailed population estimates that account for residential proximity to golf courses.

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)0.000
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 score0.845
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0070.001

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 head0.022
GPT teacher head0.207
Teacher spread0.185 · 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