MétaCan
Menu
Back to cohort

Sumario

2019· article· es· W4248274273 on OpenAlexfundno aff
Emilio Álvarez Arregui

Bibliographic record

VenueAula Abierta · 2019
Typearticle
Languagees
Field
Topic
Canadian institutionsnot available
FundersUniversidad de LeónUniversidad de SalamancaUniversity of ThessalyPontificia Universidad Católica de ChileUniversité Nice Sophia AntipolisUniversity of Illinois at Urbana-ChampaignUniversidad de DeustoUniversidade do MinhoUniversidad de AlmeríaUniversidad de CádizUniversidad de CórdobaUniversidad de ValladolidUniversitat de les Illes BalearsUniversität zu KölnBoston CollegeUniversidad de Las Palmas de Gran CanariaUniversidad de CantabriaUniversidad de MálagaUniversidad Nacional de Educación a DistanciaUniversidad de MurciaUniversidad de HuelvaEuskal Herriko UnibertsitateaUniversity of MacedoniaMcGill UniversityUniversidad Politécnica Salesiana del EcuadorUniversidad de La LagunaInstituto Tecnológico y de Estudios Superiores de MonterreyUniversidad Complutense de MadridUniversidad de JaénJohns Hopkins UniversityUniversidad de NavarraUniversity of TorontoHarvard UniversityUniversidad de SevillaUniversidad Internacional de La RiojaUniversidad de Santiago de ChileUniversidad de OviedoUniversitat Jaume I
KeywordsArt

Abstract

fetched live from OpenAlex

Sin resumen

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.385
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0030.001
Scholarly communication0.0070.002
Open science0.0020.004
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.6150.473

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 head0.007
GPT teacher head0.244
Teacher spread0.237 · 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.

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".

Quick stats

Citations0
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueAula AbiertaFrench-language works237,207