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What hope for African primate diversity?

2006· article· en· W2113059993 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.

Bibliographic record

VenueAfrican Journal of Ecology · 2006
Typearticle
Languageen
FieldPsychology
TopicPrimate Behavior and Ecology
Canadian institutionsMcGill University
FundersNational Research FoundationWildlife Conservation SocietyWorld Bank Group
KeywordsBushmeatThreatened speciesDeforestation (computer science)Extinction (optical mineralogy)PrimateGeographyBiodiversityEcologyClimate changeAgroforestryNatural resource economicsEnvironmental resource managementBiologyWildlifeHabitatEconomics

Abstract

fetched live from OpenAlex

Abstract Available empirical evidence suggests that many primate populations are increasingly threatened by anthropogenic actions and we present evidence to indicate that Africa is a continent of particular concern in terms of global primate conservation. We review the causes and consequences of decline in primate diversity in Africa and argue that the major causes of decline fall into four interrelated categories: deforestation, bushmeat harvest, disease and climate change. We go on to evaluate the rarity and distribution of species to identify those species that may be particularly vulnerable to threats and examine whether these species share any characteristic traits. Two factors are identified that suggest that our current evaluation of extinction risk may be overly optimistic; evidence suggests that the value of existing forest fragments may have been credited with greater conservation value in supporting primate populations than they actually have and it is clear that the extinction debt from historical deforestation has not being adequately considered. We use this evaluation to suggest what future actions will be advantageous to advance primate conservation in Africa and evaluate some very positive conservation gains that are currently occurring.

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)0.001
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 score0.265
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.029
GPT teacher head0.307
Teacher spread0.277 · 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