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Record W4403475279 · doi:10.3389/fcosc.2024.1457664

Behavioural ethogram to inform ex-situ initiatives for a critically endangered bird – the case of the Plains-wanderer

2024· article· en· W4403475279 on OpenAlexaff
Monique Van Sluys, Yvette Pauligk, Alicia Burns, Mark O’Riordan, Richard Matkovics, Chris Hartnett, Benjamin J. Pitcher

Bibliographic record

VenueFrontiers in Conservation Science · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsInnovation Cluster (Canada)
FundersTaronga Conservation Society Australia
KeywordsCritically endangeredEthogramEndangered speciesEx situ conservationGeographyEcologyEnvironmental resource managementEnvironmental scienceHabitatBiology

Abstract

fetched live from OpenAlex

A thorough understanding of behaviour is essential to a species recovery effort, not only to inform management and husbandry decisions, but critically, to ensure optimum survival of released animals and their offspring. The endangered Plains-wanderer, endemic to Australia and the only extant member of its family, is a bird of great conservation significance. Despite their phylogenetic uniqueness and conservation status, very little is known about their basic behavioural ecology. As part of the National Recovery efforts, an ex-situ breeding program was established to create an insurance population with the aim of releasing zoo-bred birds into their natural range. Such programs provide unique opportunities to conduct detailed behavioural and ecological studies. However, such studies are dependent on a comprehensive understanding of basic behaviour and associated social interactions, as well as a common vocabulary across institutions when it comes to describing patterns of behaviour. Therefore, a detailed ethogram is a vital first step. Here we have collated initial behavioural observations and descriptions from three main breeding institutions to create a unified ethogram across sites, with the aim of facilitating future research endeavours. Ultimately a systematic understanding of behaviour will not only improve management and conservation initiatives, but also the understanding of adaptability to potential threats going forward.

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)0.003
metaresearch head score (Gemma)0.003
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 score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.031
GPT teacher head0.300
Teacher spread0.269 · 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

Citations4
Published2024
Admission routes1
Has abstractyes

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