Bibliometric analysis of international pediatric clinical journal PEDIATRICS
Bibliographic record
Abstract
Objective To introduce the international pediatric clinical journal PEDIATRICS for pediatrics clinical medical researchers. Methods Articles of PEDIATRICS from Jan.2008 to Oct.2012 were searched through Web of Science database.Analysis in country, language, authors and frequency of subject headings based on bibliometrics methodologies was performed. Results In recent 5 years, articles of PEDIATRICS involved a total of 96 countries or regions.The United States published the most papers, 2687 of the total amount of literatures, accounted for 64.89%; followed by Canada, 295 of the literatures, accounted for 7.12%.China ranked ninth, a total of 73 papers of literature, accounted for 1.76%.Article was the most frequent type of the papers and English was the dominating language. Conclusions Currently, the researches of PEDIATRICS focus in the fields of epidemiology, care, management, influence factors, diagnosis, treatment, mortality statistics, asthma, obesity. Key words: PEDIATRICS; Bibliometrics; Journal research
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 | 0.008 | 0.073 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.140 | 0.170 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".