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Record W4312910514 · doi:10.55161/gubo2983

Capítulo 34: Impulsando las relaciones entre la selva amazónica y las ciudades globalizadas

2022· book-chapter· es· W4312910514 on OpenAlexaff
David M. Lapola, Belen Paez, Sandra Costa, Roberto Donato da Silva Júnior, Daniela M. Peluso, Paulo Moutinho, Maíra C. G. Padgurschi, Denilson Baniwa, Sônia Bridi, Nadino Calapucha, Zienhe Castro, Fander Falconí, Mapulu Kamayurá, Eduardo Kohn, Anderson Mattos, Pedro Meloni Nassar, Laurent Troost, Manari Ushigua, Robert B. Wallace, Marko Zangas

Bibliographic record

VenueUN Sustainable Development Solutions Network (SDSN) eBooks · 2022
Typebook-chapter
Languagees
FieldHealth Professions
TopicIndigenous Health and Education
Canadian institutionsMcGill University
Fundersnot available
KeywordsGeographyAmazon rainforestHumanitiesForestryArtBiology

Abstract

fetched live from OpenAlex

Al brindar una revisión breve y no autorizada de las relaciones físicas y culturales entre las áreas rural/forestal y urbana en la Amazonía, identificamos varios aspectos a mejorar, como subsidiar la residencia de largo plazo de los profesionales de la salud en el campo, implementar cinturones agrícolas/extractivistas peri-urbanos para la seguridad alimentaria en las ciudades, aumentar la penetración de los bosques y espacios verdes en los paisajes urbanos amazónicos, invertir en innovación en torno al concepto de “ciudades inteligentes-bosques inteligentes” y, quizás lo más importante, movilizar recursos humanos, financieros y recursos institucionales para propiciar una resignificación o refundación de los vínculos culturales, espirituales y afectivos de los habitantes urbanos con el bosque, apoyados en la gente del bosque y sus cosmovisiones.

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)0.006
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.842
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0300.001
Scholarly communication0.0000.000
Open science0.0010.002
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0090.002

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 head0.025
GPT teacher head0.296
Teacher spread0.271 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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

Explore more

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