Morphology in the last 10 years: a bibliometric analysis
Bibliographic record
Abstract
Purpose: Morphology is the science of structure, function and development. Many different disciplines work in this field of science. Bibliometric analysis is a method that examines the productivity, efficiency and performance of factors such as author, country and university. Materials and methods: In this study, the researches conducted in the field of morphology in the last 10 years were analyzed bibliometrically. Results: It was analyzed that 83214 studies were conducted in the last 10 years, the most studies were conducted at the Temerty Faculty of Medicine of the University of Toronto, the United States of America as the country and SCI-Expanded index. Elsevier publishing house is the most used publishing house and neuroscience is the field of science with the highest number of publications. Conclusion: Studies in the field of morphology, which has shed light on other branches of science throughout history, have been increasing in the last 10 years. In our study, it is aimed to guide scientists who will conduct research in the field of morphology in the future.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.106 | 0.126 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".