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Record W1513312170 · doi:10.4000/jsa.12203

López Luján Leonardo y Guilhem Olivier (eds), El sacrificio humano en la tradición religiosa mesoamericana

2012· article· es· W1513312170 on OpenAlexaboutno aff
Nathalie Ragot

Bibliographic record

VenueJournal de la Société des Américanistes · 2012
Typearticle
Languagees
FieldArts and Humanities
TopicLatin American history and culture
Canadian institutionsnot available
Fundersnot available
KeywordsArtHumanities

Abstract

fetched live from OpenAlex

p., ill., photos 1 Ce gros livre de presque 600 pages est la publication des interventions d'un aréopage de 28 scientifiques internationaux (Mexicains, Belge, Français, Japonais, Canadiens, Nord-Américains) réunis à Mexico en septembre 2007 pour un séminaire consacré au sacrifice humain.L'objectif principal de cet ouvrage est de présenter les nouvelles avancées sur les significations, les fonctions et l'évolution historique du sacrifice humain en Mésoamérique en considérant les informations émanant de diverses disciplines : archéologie, anthropologie physique, biologie, histoire des religions et ethnologie.Comme le souligne Alicia Mayer, directrice de l'Instituto de investigaciones históricas de la UNAM, dans l'introduction, « les fonctions et les significations du sacrifice humain sont nombreuses et varient en fonction des participants et des contextes rituels ; cet événement ne peut être réduit à des interprétations univoques et il est nécessaire de l'analyser dans le cadre de ses différents contextes historiques » (p.18).À cette fin, les interventions rendent compte des multiples expressions du sacrifice dans des géographies et à des époques différentes, allant du Préclassique à la période contemporaine, tout en couvrant la majeure partie du territoire mésoaméricain, des chaudes terres mayas du Sud aux arides terres du Nord.

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)0.001
metaresearch head score (Gemma)0.000
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: Review · Consensus signal: Review
Teacher disagreement score0.030
Threshold uncertainty score0.060

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.002
Scholarly communication0.0030.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.001

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 head0.013
GPT teacher head0.282
Teacher spread0.269 · 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
GenreReview

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

Citations3
Published2012
Admission routes1
Has abstractyes

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