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Record W2293232654 · doi:10.22456/2236-3254.45827

COEUR EN TÊTEO: COM A CABEÇA NO CORAÇÃO

2014· article· pt· W2293232654 on OpenAlexaff
Sylvie Fortin

Bibliographic record

VenueCena · 2014
Typearticle
Languagept
FieldArts and Humanities
TopicCultural, Media, and Literary Studies
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsArtHumanities

Abstract

fetched live from OpenAlex

O título dessa entrevista – Cœur en tête – é o mesmo de um evento beneficente organizado por Nathalie Buisson com o objetivo de obter fundos para apoiar a pesquisa sobre câncer no cérebro. Na entrevista, Nathalie Buisson conversa com Christine Hanrahan sobre essa doença que atinge as duas e que as leva a refletir sobre as possíveis relações entre essa experiência e a dança. Nathalie, na época da entrevista tinha 41 anos. Ela foi bailarina clássica e contemporânea e trabalhou como ensaiadora em companhias de nível internacional. Christine tinha 53 anos. Ela também foi bailarina contemporânea e professora de dança e atuou como psicóloga clínica com ênfase em na performance artística. A entrevista foi conduzida por Sylvie Fortin e revisada por ela e por Christiane Hanrahan.

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)0.003
metaresearch head score (Gemma)0.009
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: none
Teacher disagreement score0.022
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0110.025
Scholarly communication0.0140.012
Open science0.0010.007
Research integrity0.0050.010
Insufficient payload (model declined to judge)0.0120.002

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 head0.022
GPT teacher head0.221
Teacher spread0.199 · 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
Published2014
Admission routes1
Has abstractyes

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