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Record W2117654162 · doi:10.1139/juvs-2014-0014

Evaluation of UAS for photographic re-identification of bowhead whales,<i>Balaena mysticetus</i>

2015· article· en· W2117654162 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.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Unmanned Vehicle Systems · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsFisheries and Oceans CanadaASL Environmental Sciences (Canada)
Fundersnot available
KeywordsAerial surveyGeographyPopulationWhalingFisheryRemote sensingArchaeologyBiology

Abstract

fetched live from OpenAlex

Unmanned aerial systems (UAS) have the potential to collect high-resolution photographs of marine mammals for life-history studies without disturbing the species being studied. We conducted a pilot study near Igloolik, Nunavut, in early July 2013 to collect identification-quality photographs of bowhead whales and record the responses of the whales to overflights by an UAS. Operating under a restrictive line-of-sight permit from Transport Canada, we successfully collected high quality photographs of bowhead whales and none of the whales overflown responded to the overflights in an observable manner. If the UAS were operated under a beyond-line-of-sight permit, the UAS could be used to search for whales ahead of and to the side of the survey vessels making it more efficient to find whales to photograph. Even when operating under the restrictive line-of-sight permit, large numbers of whales could be photographed, which would provide important life-history information on the poorly studied Eastern Canada – West Greenland population.

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)0.008
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.261
Threshold uncertainty score0.445

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.001
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)0.0000.000

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 head0.079
GPT teacher head0.309
Teacher spread0.230 · 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