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Record W2799741528 · doi:10.3145/thinkepi.2018.49

Los medios sociales en la comunicación científica

2018· article· es· W2799741528 on OpenAlex
My current institution is not University of Wisconsin–Madison, but Universidad de León (Spain).

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueAnuario ThinkEPI · 2018
Typearticle
Languagees
FieldSocial Sciences
TopicCommunication and COVID-19 Impact
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

La conversación se ha trasladado a los medios sociales, también en el ámbito de la comunicación científica. En los últimos años, se viene analizando cómo los investigadores utilizan los medios sociales y cómo difunden los resultados de investigación y se han introducido las métricas alternativas, que más bien parecen complementarias. Un estudio del Canada Research Chair on the Transformations of Scholarly Communication, de la Université de Montreal, comisionado por el Social Sciences and Humanities Research Council (SSHRC), aporta un amplio estado de la cuestión sobre el tema que resulta muy útil para conocer los diferentes puntos de vista abordados en la bibliografía. Además, este trabajo incluye un análisis del uso de Twitter por parte de los receptores de los premios doctorales del SSHRC.

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.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesScience and technology studies, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.886
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.003
Scholarly communication0.0010.000
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.058
GPT teacher head0.399
Teacher spread0.341 · 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