MétaCan
Menu
Back to cohort
Record W2003349472 · doi:10.1071/wr03072

Use of infrared digital cameras to investigate the behaviour of cryptic species

2004· article· en· W2003349472 on OpenAlexaff
Andrew W. Claridge, Greg Mifsud, J. P. Dawson, Michael J. Saxon

Bibliographic record

VenueWildlife Research · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsDepartment of Environment and Conservation
FundersNational Parks and Wildlife ServiceNational Park Service
KeywordsCarnivoreEndangered speciesSpecies complexNational parkEcologyGeographyBiodiversityRemote sensingBiology

Abstract

fetched live from OpenAlex

In this paper we report on the application of infrared digital cameras to investigate aspects of the breeding biology of the spotted-tailed quoll, an endangered marsupial carnivore. Technical details are provided about the cameras, which were deployed remotely at two ‘latrine’ sites used by the target species within Kosciuszko National Park in southern New South Wales, Australia. Examples of images captured by the cameras are presented, with notes on possible application of the same technology to better understand the social behaviour of rare and cryptic species.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.099
GPT teacher head0.308
Teacher spread0.209 · 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

Citations104
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueWildlife ResearchSame topicWildlife Ecology and ConservationFrench-language works237,207