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Record W4231571489 · doi:10.22490/24629448.1721

Editorial

2016· editorial· es· W4231571489 on OpenAlexaff
Olga-Lucía Ostos-Ortiz

Bibliographic record

VenueNova · 2016
Typeeditorial
Languagees
FieldMedicine
TopicHealth and Medical Research Impacts
Canadian institutionsImpact
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

La Revista NOVA, Publicación Científica en Ciencias Biomédicas, se articula a la dinámica mundial de medición de impacto y visibilidad de las publicaciones científicas. En este contexto, es fundamental que nuestros lectores se familiaricen con dichos factores de impacto.El factor de impacto (FI) de una revista en un ano determinado, se obtiene de dividir el número de citaciones recibidas por los artículos de esa revista en los dos o tres años inmediatamente anteriores, por el número total de publicaciones de la revista durante ese mismo periodo de tiempo. Esta métrica fue desarrollada e implementada en la publicación del Science Citation Index y desde entonces, el FI se ha convertido en una de las métricas de mayor influencia en el campo de la cienciometria.

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)0.004
metaresearch head score (Gemma)0.387
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.383
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.387
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0080.018

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 head0.101
GPT teacher head0.471
Teacher spread0.370 · 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
GenreEditorial

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
Published2016
Admission routes1
Has abstractyes

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