MétaCan
Menu
Back to cohort

Considerações sobre as relações entre a análise de citação e a pesquisa científica colaborativa

2009· article· pt· W2015657488 on OpenAlex
Márcia de Oliveira Teixeira, Carlos José Saldanha Machado, Ana Tereza Pinto Filipecki, Lía Hasenclever, Helena Espellet Klein

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueTransinformação · 2009
Typearticle
Languagept
FieldDecision Sciences
TopicBusiness and Management Studies
Canadian institutionsDiscovery Air (Canada)
FundersFundação Oswaldo Cruz
KeywordsHumanitiesPhilosophyPolitical science

Abstract

fetched live from OpenAlex

Agências de fomento governamentais e organismos internacionais estimulam programas de pesquisas científicas colaborativas. E um dos principais argumentos são os seus benefícios para o aumento da produtividade científica. Segundo a literatura especializada, as colaborações científicas, ao fortalecerem as dimensões multi e interdisciplinar, potencializam o incremento da produção de inovações técnico-científicas em diferentes setores. Assim se deu o crescimento do interesse nos indicadores de produtividade das colaborações, sendo os mais difundidos apoiados na análise da citação. Todavia até que ponto as medições baseadas nessa análise nos permitem dimensionar os efeitos das colaborações científicas na produção e no conteúdo de conhecimentos científicos? O objetivo deste trabalho é discutir os limites da análise da citação para a avaliação de iniciativas de pesquisa científica colaborativa, a partir da revisão de proposições da literatura especializada.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient 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 score0.741
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0010.000
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.052
GPT teacher head0.337
Teacher spread0.285 · 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