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Record W1991955333 · doi:10.1080/15287394.2011.618988

The Impact of Chronic Wasting Disease and its Management on Hunter Perceptions, Opinions, and Behaviors in Alberta, Canada

2011· article· en· W1991955333 on OpenAlexaffabout
Natalie Zimmer, Peter C. Boxall, Wiktor Adamowicz

Bibliographic record

VenueJournal of Toxicology and Environmental Health · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPrion Diseases and Protein Misfolding
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsChronic wasting diseaseTRIPS architectureRespondentResidenceGeographySocioeconomicsBusinessRisk perceptionDemographyPsychologyDemographic economicsPerceptionMarketingEconomicsTransport engineeringMedicineDiseasePolitical scienceSociologyEngineering

Abstract

fetched live from OpenAlex

The goal of this analysis was to identify changes in hunting behavior, satisfaction, and perceptions of risk in the presence of chronic wasting disease (CWD). Hunters completed an Internet survey containing direct questions regarding the impacts of CWD and gathering information about real and hypothetical hunting trips. Overall, hunters were satisfied with CWD management, and although certain behaviors were altered, the perceived risk by hunters did not seem to be high. A travel cost model was used to determine whether differences in trip frequencies might be observed in response to CWD. The largest variation in trips was between urban and rural hunters, with urban hunters being less averse to traveling but more averse to CWD and the management program of extra tags.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.103

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.009
GPT teacher head0.267
Teacher spread0.258 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations15
Published2011
Admission routes2
Has abstractyes

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