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Record W2761802483

INVESTIGACIÓN MUNDIAL SOBRE EL ORIGEN DEL HOMO SAPIENS. LA ENCABEZA LA UNIVERSIDAD

2017· article· es· W2761802483 on OpenAlexaboutno aff
Leonardo Frías

Bibliographic record

VenueGaceta UNAM (2010-2019) · 2017
Typearticle
Languagees
FieldSocial Sciences
TopicLatin American Cultural Politics
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesHomo sapiensGeographyPolitical scienceArtArchaeology
DOInot available

Abstract

fetched live from OpenAlex

LA UNAM, MEDIANTE EL INSTITUTO DE INVESTIGACIONES ANTROPOLOGICAS (IIA), CONTINUA CON LA EJECUCION DEL PROYECTO INTERNACIONAL OCUPACION TEMPRANA DE HOMO SAPIENS EN LA PLUVISELVA TROPICAL DE GUINEA ECUATORIAL: RIFT DE UORO-RIO WELE, EL CUAL ES ENCABEZADO POR ALEJANDRO TERRAZAS MATA, DEL LABORATORIO DE PREHISTORIA Y EVOLUCION HUMANA. SE TRATA DEL PRIMER GRAN TRABAJO GLOBAL DEDICADO A ENTENDER COMO Y POR QUE SE GENERO EL HOMO SAPIENS , ASI COMO INDAGAR Y COMPRENDER COMO PARTICIPO UNA TERCERA PARTE DEL CONTINENTE AFRICANO, ES DECIR, SUS SELVAS TROPICALES, EN EL ORIGEN DE NUESTRA ESPECIE. “POR VEZ PRIMERA UN PROYECTO DE PALEOANTROPOLOGIA MEXICANO SE DESARROLLA EN EL CONTINENTE AFRICANO Y ES CIEN POR CIENTO COORDINADO DESDE NUESTRO PAIS, AUN CON COLABORADORES DEL AMBITO INTERNACIONAL”, DIJO TERRAZAS MATA, PREVIO A SU PARTIDA A AFRICA CENTRAL. INTERVIENEN TAMBIEN BOTANICOS Y ANTROPOLOGOS DE LA UNIVERSIDAD NACIONAL DE GUINEA ECUATORIAL, ASI COMO DE LAS UNIVERSIDADES DE CALGARY, CANADA; BERKELEY, ESTADOS UNIDOS, E INSTITUCIONES DE EDUCACION SUPERIOR DE ESPANA. EN LA PARTE DE LA GENERACION Y PROCESO DEL CONOCIMIENTO EN LABORATORIOS EN MEXICO, PARTICIPAN 17 UNIVERSITARIOS INTEGRANTES DEL IIA, ASI COMO DE LOS INSTITUTOS DE FISICA, DE GEOFISICA Y DE GEOLOGIA DE LA UNAM. ADEMAS DE LA LABOR INTERINSTITUCIONAL CON ACADEMICOS DE LA ESCUELA NACIONAL DE ANTROPOLOGIA E HISTORIA. ALEJANDRO TERRAZAS NARRA EL ORIGEN Y DESARROLLO DE DICHO PROYECTO.

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)0.002
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: Other · Consensus signal: none
Teacher disagreement score0.020
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.005
Scholarly communication0.0040.002
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.024
GPT teacher head0.317
Teacher spread0.293 · 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
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".

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Citations0
Published2017
Admission routes1
Has abstractyes

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