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Record W4321512961 · doi:10.58807/tmptvm20224871

En el saber indígena las plantas son una fuente de enseñanza

2022· article· es· W4321512961 on OpenAlexaboutno aff
Jeremy Narby

Bibliographic record

VenueTemperamentvm · 2022
Typearticle
Languagees
FieldSocial Sciences
TopicIndigenous Cultures and Socio-Education
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesAmazon rainforestPhilosophyArtGeographyBiologyEcology

Abstract

fetched live from OpenAlex

Creció en Montreal (Quebec) y en Suiza, y más tarde estudió Historia en la Universidad de Kent y se doctoró en Antropología en la Universidad de Stanford. Ha vivido durante años con los indígenas asháninca de la Amazonia peruana, estudiando su relación con la selva y apoyando su combate contra la masacre ecológica en marcha. En sus libros, Narby examina la relación y los posibles puentes entre el chamanismo y la ciencia, especialmente desde el punto de vista de la biología molecular. Autor de La serpiente cósmica, Intelligence in Nature, Shamans Through Time y Plant Teachers: Ayahuasca, Tobacco, and the Pursuit of Knowledge.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.800
Threshold uncertainty score0.402

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0080.003
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0130.001

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 head0.010
GPT teacher head0.328
Teacher spread0.318 · 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 designNot applicable
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

Citations0
Published2022
Admission routes1
Has abstractyes

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