Publication, citations, and impact factors of leading investigators in critical care medicine.
Bibliographic record
Abstract
INTRODUCTION: Critical care medicine research is reported in major medical journals that can be accessed via computerized search engines such as PubMed (National Library of Medicine) or Web of Science (Thomson ISI [Institute for Scientific Information]). The crediting of report citations to specific journals or individuals is a rapidly developing and highly controversial evaluative process. METHODS: We conducted a citation analysis to measure the research and publication accomplishments of critical care medicine investigators, by tallying their numbers of published reports and numbers of citations to their reports. Major investigators were identified from the author indexes of major critical care medicine publications. From the Web of Science the number of publications and citations of their works were determined for 224 investigators for the period 1997 through August 2003. We calculated the individual researcher's "impact factor" by dividing the number of citations (made by other researchers to a given researcher's reports) by the number of articles that researcher had published. To estimate which countries are producing the most research on mechanical ventilation, we studied the abstract books from the 2001, 2002, and 2003 American Thoracic Society annual international conferences and tallied the number of posters (pertaining to mechanical ventilation) from the various countries. We then calculated a "country factor" as the number of posters per million population of the source country. RESULTS: We considered 44, 576 citations in 3,755 publications. Using criteria selected to recognize original works, J L Vincent published the greatest number of reports (129). M A Matthay received the most citations (2,056). G U Meduri had the highest impact factor (25.32). There was a balance between the number of leading investigators from Europe and North America. Relative to its population size, Canada warrants leadership acknowledgement in critical care medicine, considering its number of leading investigators and poster presentations. CONCLUSIONS: From criteria selected to attribute original work to specific authors we identified 20 leading critical care medicine investigators, as measured by number of publications, citations, and impact factors. We also report a country factor based on posters (on mechanical ventilation) presented at the 2001-2003 international conferences of the American Thoracic Society.
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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 | 0.029 | 0.241 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.031 | 0.049 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".