Highly Cited Works on Human Clinical Trials
Bibliographic record
Abstract
The aim of this study was to determine landscapes of the most cited publications on Human Clinical Trials. The top 856 most cited publications on Human Clinical Trials were identified from Web of Science database. The 856 most cited papers on Human Clinical Trials were published between 1989 and 2021 with an average Citation per paper is 1065.46 (Citations range: 400–6319) and are included among the 56 most cited papers in in New England Journal of Medicine with 50851 Citations followed by Journal of Clinical Oncology with 43200 Citations, JAMA Journal of the American Medical Association with 28875 Citations, Nature with 26456 and Lancet with 25181 Citations. The most Cited Countries are: USA with 453423 Citations followed by UK with 100930 Citations, Canada with 84220, France with 61930, Germany with 61752 and India ranked 31st Place according to Citations with 4409. The most cited publications on Human Clinical Trials are highly impactful, landmark studies representing Institutions, Countries, Sources and authorship pattern. A clinical trial is a research study in human volunteers to answer specific health questions. Carefully conducted clinical trials are fastest and safest way to find treatment that work in people and way to improve health. These influential publications have immensely inspiration research for invention of Drugs, Vaccines and Medicines.
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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 | 0.021 | 0.130 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.056 | 0.092 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.012 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.041 | 0.010 |
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".