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Record W4206259381 · doi:10.1111/conl.12860

Using nonhuman culture in conservation requires careful and concerted action

2022· article· en· W4206259381 on OpenAlex
Susana Carvalho, Erin G. Wessling, Ekwoge E. Abwe, Katarina Almeida‐Warren, Mimi Arandjelovic, Christophe Boesch, Emmanuel Danquah, Catherine Hobaiter, Kimberley J. Hockings, Tatyana Humle, Rachel Ashegbofe Ikemeh, Ammie K. Kalan, Lydia V. Luncz, Gaku Ohashi, Alejandra Pascual‐Garrido, A. Piel, Liran Samuni, Serge Soiret, Crickette Sanz, Kathelijne Koops

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

VenueConservation Letters · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsAction (physics)Endangered speciesSet (abstract data type)Environmental resource managementEnvironmental ethicsConservation scienceEnvironmental planningNature ConservationBusinessEngineering ethicsPolitical scienceComputer scienceEcologyBiodiversityBiologyGeographyEngineeringHabitatEnvironmental science

Abstract

fetched live from OpenAlex

Abstract Discussions of how animal culture can aid the conservation crisis are burgeoning. As scientists and conservationists working to protect endangered species, we call for reflection on how the culture concept may be applied in practice. Here, we discuss both the potential benefits and potential shortcomings of applying the animal culture concept, and propose a set of achievable milestones that will help guide and ensure its effective integration existing conservation frameworks, such as Adaptive Management cycles or Open Standards.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.051
Threshold uncertainty score0.789

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 head0.050
GPT teacher head0.274
Teacher spread0.223 · 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