Evolution of the Scientific Literature of Cytochrome P450 from 1977 to 2008
Bibliographic record
Abstract
This study traces the evolution of the scientific literature on cytochrome P450 (P450) published during the last 30+ years (1977-2008). Using the Web of Science, P450 articles from the Science Citation Index Expanded published from 1977 to 2008 were retrieved and analyzed. The number of P450 papers has increased from 342 articles in 1977-1978 to 2,357 in 2007-2008, and the number of contributing countries has grown from 23 countries for 1977-1978 to 76 for 2007-2008. While the USA and Japan were the most productive countries, along with several industrialized countries (e.g. UK, Germany and Canada), two Asian countries have recently joined the group of leading countries (in 2007-2008 China ranked 4th and South Korea, 7th). During 1977-2008, the number of journals publishing papers in P450 research increased more than seven-fold (7.7): 94 journals in 1977-1978 and 724 in 2007-2008; however, citation by readers (as measured by the journal impact factor) of the top-ten leading journals increased only slightly from 3.25 for 1977-1978 to 3.81 for 2007-2008. While Biochemistry & Molecular Biology and Pharmacology and Pharmacy are the two main targeted subject areas for P450 research during the period considered, there has been a gradual shift from the biophysical and biochemical fields of interest to aspects of genomics and clinical approaches. The rapid evolution of P450 research in the last 30+ years was accompanied by important changes in the landscape of the contributing countries, in the subject domains, and consequently in the scientific journals targeted by researchers.
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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 | 0.007 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.055 | 0.055 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".