Institutionalization of research on community-acquired pneumonia // Институционализация на изследванията върху пневмонията, придобита в обществото
Bibliographic record
Abstract
Problem-oriented scientometric investigations of the institutionalization, interdisciplinarity and internationalization of science contribute to enhancement of the quality and effectiveness of research activity at the forefront of science. Recently, the interest in the community-acquired pneumonia (CAP) impetuously runs high that leads to a more intensive publication activity in the whole world. A retrospective on-line literature search on these problems in the data-bases (information portals) Web of Science (WoS), Scopus, EMBASE, and MEDLINE (through EBSCO) in 1985-2008 was carried out. The following indicators were analyzed: number of abstracted publications per years; languages of publications; number of authors of these publications; number of countries of these authors; number of journals with these publications;document types; publications by Bulgarian authors;number of authors’ scientific institutions; authors and institutions presenting with the greatest number of publications as well as most-commonly cited authors. The total number of abstracted publications is 8748 in Scopus, 8009 in EMBASE, 6766 in WoS, and 4213 in MEDLINE. The numbers of abstracts, authors, journals, and institutions rise uninterruptedly. The journals Clinical Infectious Diseases and Chest, the University of Pittsburgh and Winthrop University Hospital as well as the most productive and most commonly cited authors T. J. Marrie (Canada), A.Torres (Spain) and T. M. File (US A) have been sharply outlined. Bulgaria presents only with 8 articles in 5 Bulgarian journals and with two articles in one eminent foreign journal. The created bibliographic and abstracting data-base can be used by Bulgarian investigators of the problems of CAP for the purposes of fruitful international collaboration.
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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 | 0.024 | 0.058 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.017 | 0.025 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".