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Record W7133270098

Environmental factors and behaviour of St. Lawrence Estuary Beluga generate heterogeneity in availability bias for photographic and visual aerial surveys

2024· other· en· W7133270098 on OpenAlexfundno aff
Véronique Lesage, Sara Wing, Alain F. Zuur, Jean-François Gosselin, Arnaud Mosnier, Anne St-Pierre, Robert Michaud, Dominique Berteaux

Bibliographic record

VenueFederal Open Science Repository of Canada / Le Dépôt fédéral de science ouverte du Canada · 2024
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
FundersFisheries and Oceans Canada
KeywordsBelugaEstuaryVisibilityAerial surveyAbundance (ecology)Beluga WhaleObserver (physics)
DOInot available

Abstract

fetched live from OpenAlex

In absence of adequate data, abundance estimates for St. Lawrence Estuary (SLE) beluga obtained from visual surveys have been corrected for availability bias using factors developed for photographic surveys. Not accounting for the longer detection time associated with visual surveys will lead to an overestimation of beluga abundance relative to indices obtained from photographic surveys. This study offers a comprehensive analysis of the relative influence of multiple methodological, environmental and behavioural factors on availability bias estimates for both photographic and visual surveys using detailed dive profiles from 27 SLE beluga. As expected, availability estimates were systematically higher for visual surveys than for photographic surveys for which time-in-view is instantaneous. However, for photographic surveys the change in methodology for estimating availability from an approach based on group visibility to one where the detailed diving patterns of individuals were logged, led to a 26—42% decrease in mean availability estimates. Our results confirmed that dives are longer when animals are inside compared to outside areas of high density (AHD), consistent with the prediction that these areas are used for behaviour like foraging. They also indicate that while some of the behavioural or environmental factors such as latent processes associated with the zone used may have a notable effect on availability, survey design (photographic or visual), characteristics of survey platforms, and observer searching patterns may be the most influential factors on availability bias. We conclude that previous estimates of SLE beluga abundance from photographic surveys were likely biased downward by an overestimation of beluga availability, and by not considering the uneven distribution of beluga among different zones with specific but undefined underlying processes.

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)0.002
metaresearch head score (Gemma)0.006
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 score0.960
Threshold uncertainty score0.079

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.018
GPT teacher head0.253
Teacher spread0.235 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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Same venueFederal Open Science Repository of Canada / Le Dépôt fédéral de science ouverte du CanadaFrench-language works237,207