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Record W2067070436 · doi:10.1080/10871209.2012.661028

Wildlife Sightings at Western Canadian Regional Airports: Implications for Risk Analyses

2012· article· en· W2067070436 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

VenueHuman Dimensions of Wildlife · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsPositive Living NorthUniversity of Northern British ColumbiaRaincoast Conservation Foundation
Fundersnot available
KeywordsWildlifeDue diligenceGeographyUngulateWildlife managementEnvironmental resource managementFisheryBusinessEcologyHabitatEnvironmental scienceFinance

Abstract

fetched live from OpenAlex

Aircraft collisions with wildlife result in substantial personal and economic losses, requiring airport authorities to utilize all available resources to develop effective management strategies. We surveyed 16 western Canadian regional airports to document the use of wildlife strike and sighting records (WSSRs). Ninety-four percent of airports kept wildlife strike records, 19% kept bird sighting records and 25% kept animal sighting records. Of 12 airports, 33% used WSSRs to identify problem species or trends and 25% used WSSRs for risk analysis and management planning. Our findings suggest that WSSRs are underutilized in risk analyses and ungulate strike risk may be underestimated at most respondent airports. Airport mangers must stress due diligence in record keeping and the application of wildlife data to support risk analyses and sound wildlife management practices at airports.

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.050
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 studies0.0010.000
Scholarly communication0.0000.000
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 head0.065
GPT teacher head0.325
Teacher spread0.260 · 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