When Neuroscience Meets Pharmacology: A Neuropharmacology Literature Analysis
Bibliographic record
Abstract
Background: Considering the enormous progress in the field of neuropharmacology and its global importance, as well as the lack of bibliometric studies examining this field as a whole, it is a high time to assess the prevailing topics and citation performances of its research works. Methods: Web of Science (WoS) was searched to identify relevant neuropharmacology articles, which were analyzed with reference to (1) publication year, (2) journal title, (3) total citation count, (4) authorship, (5) WoS category, and (6) manuscript type. The identified manuscripts were analyzed with VOSviewer for further bibliometric parameters, such as citation analysis of institutions, countries/regions, and journals, and to visualize the citation patterns of the terms appearing in the titles and abstracts. Results: The literature search resulted in 43,354 manuscripts. Nearly 98% of them were published since the 1990s. The majority of the manuscripts were original articles (n = 31,360) and reviews (n = 11,266). The top five WoS categories associated with the analyzed manuscripts were Pharmacology/Pharmacy (n = 14,892, 34.3%), Neurosciences (n = 11,747, 27.1%), Clinical Neurology (n = 4,981, 11.5%), Psychiatry (n = 4,464, 10.3%), and Biochemistry/Molecular Biology (n = 4,337, 10.0%). Seven of the top ten most prolific institutions were located in the USA, and one each in Canada, Italy and the UK, respectively. Manuscripts mentioning certain molecules or pharmaceuticals had high citations per manuscript, such as those reporting about anandamide, tetrahydrocannabinol, L-glutamate, clozapine, and curcumin. These terms with at least 50 citations per manuscript were mostly related to cannabis and anti-psychotic drugs, with some dealing with anti-epilepsy effects and Alzheimer’s disease. Conclusion: We have identified and analyzed all neuropharmacology articles published since the 1990s. Importantly, the area of neuropharmacology research has been growing steadily due to the global trend in population ageing and associated with this continuously increasing number of patients with neuropsychiatric disorders worldwide. It is hoped that identification of new pharmaceutically useful molecules or new clinical applications will continue in the future, in order to improve clinical outcomes and to further strengthen the field of neuropharmacology, a research area cross-linking basic and clinical sciences.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".