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Record W2962845282 · doi:10.1016/j.japb.2019.07.005

Threats to the populations of two endemic brushturkey species in Indonesian New Guinea

2019· article· en· W2962845282 on OpenAlexfundno aff
Margaretha Pangau‐Adam, Jedediah F. Brodie

Bibliographic record

VenueJournal of Asia-Pacific Biodiversity · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaGeorg-August-Universität GöttingenCanada Foundation for Innovation
KeywordsDeforestation (computer science)Threatened speciesEndangered speciesEcologyLoggingAbundance (ecology)GeographyOccupancyHabitat destructionDisturbance (geology)HabitatNew guineaIndonesianPopulationCritically endangeredEndemismBiologyEthnologyDemography

Abstract

fetched live from OpenAlex

Half of megapode bird species occur in New Guinea and adjacent islands, and almost all of the species are endemic to this region. Despite rapid regional development and deforestation in New Guinea, little is known about the population ecology of these birds, many of which are threatened or endangered. We used camera traps to assess impacts of anthropogenic disturbance and introduced predators on the occurrence and local abundance of red-legged brushturkey Talegalla jobiensis in lowland forests of Nimbokrang, Papua, and the wattled brushturkey Aepypodius arfakianus in the Arfak mountains, West Papua, Indonesia. In hierarchical occupancy models, detection rates were higher in logged forest for both brushturkey species. Occurrence rates of brushturkeys were not affected by logging, hunting pressure, or pig abundance. However, as degradation of megapode habitat is increasing across New Guinea, it is predicted that concurrent pressures from two or more of these threats could affect the distribution and populations of brushturkeys.

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 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 score0.020
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 studies0.0000.000
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 head0.030
GPT teacher head0.236
Teacher spread0.206 · 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 teacher head, not a consensus.

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

Citations7
Published2019
Admission routes1
Has abstractyes

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