Publication rules in biomedical journals: their compliance with the “test of nine”
Bibliographic record
Abstract
Descreve o resultado de pesquisa sobre se as regras de publicação de periódicos biomédicos são fonte segura para orientar autores de artigos no ajuste de itens de manuscritos a serem submetidos. Trata-se de estudo quantitativo cujos objetivos foram identificar os elementos essenciais na composição das palavras-chave, citações e referências e avaliar a conformidade das regras de publicação das revistas comparando-as com a estrutura dos artigos publicados nos fascículos mais recentes. Procedimentos denominados pelo autor como sendo a “Prova dos nove”. Foram incluídas na pesquisa revistas de Dermatologia que seguem as recomendações do International Committee of Medical Journal Editors e que disponibilizam suas regras em português, inglês, francês ou espanhol. A análise das 24 revistas incluídas no estudo mostrou que as regras de publicação não são totalmente observadas pelas revistas de dermatologia que informam seguir as recomendações da norma de Vancouver, sendo necessário, para uma maior segurança dos autores, consultar os artigos mais recentes,a fim de utilizá-los como orientação adicional na formatação de seus manuscritos.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.450 | 0.812 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.016 | 0.016 |
| Science and technology studies | 0.007 | 0.019 |
| Scholarly communication | 0.020 | 0.015 |
| Open science | 0.006 | 0.011 |
| Research integrity | 0.008 | 0.009 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".