The effect of key characteristics of the title and morphological features of published articles on their citation rates
Bibliographic record
Abstract
The title is one of the most important parts of the article because it is the first contact that reviewers and readers have with the paper. This study aimed to evaluate the effect of key characteristics of the title and morphological features of articles on their citation rates. One thousand two hundred and fifty one articles published in eight ISI-indexed reputable journals were analyzed. A form was designed to collect information on the number of citations in the Scopus, characteristics of the title and morphological features of each article. The results revealed that the title type, number of words and characters in the title were not correlated with the number of citations (P>0.05). Also, the authors’ country of origin and mentioning time in the title were not associated with the number of citations (P>0.05). A significant relationship was found between types of articles and number of citations (P<0.001); the average number of citations for review articles was higher than original articles. The average number of authors was positively and significantly correlated with the average number of citations (P<0.001). Moreover, the average number of citations was considerably higher in the articles with no reference to the place of the study in the title (P<0.001). The results showed that some characteristics of the articles and their titles such as types of articles, number of authors and reference to the place in the title affect the citation rates of published articles.
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 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".