A Survey of Accuracy of Cited Articles Based Theses of Medical Specialities Students in Tehran University of Medical Sciences
Bibliographic record
Abstract
Background and Aim: Citation could be considered as basis of scientific researches. Each researcher will use citation to prove his scientific findings either to be in correspondence with truth or to familiarize readers with more references. Maintenance and continuation of informational link by citation is essential. Theses are not exceptional for this subject. This study was done to review the accuracy of cited articles of specialized theses (Tehran University of Medical Sciences in 1386) and the rate of correspondence with Vancouver style.Materials and Methods: Citation analysis is used as study approach. By systematic sampling and Morgan table 357 cited articles were selected to review for accuracy of citation and their correspondence with Vancouver style. Six studied factors are as following: Name of author(s), title of article, title of journal, year of Publishing, volume number, number of pages. Citation errors are divided in to two main groups: 1-Minor errors 2-Major errors. Method of sampling is direct observation. Data was entered in a check list, based on Taylor division. SPSS(11.0) software was used to analysis.Results: Out of all 357 reviewed cited articles, totally 111.4% citation errors were observed and only 136 (38.09%) of citations had no error and 221(62%) citations had errors. 9.8% of citations fully corresponded with Vancouver style.Discussion and Conclusions: Main reasons of dissatisfying results of citation errors and rate of correspondence with Vancouver style are as follows: Student's unawareness of importance of scientific researches consistence Laxity of students about citification produce, inaccessibility to original references and copy of other sources.Teacher's less emphasis on accuracy of citation, carelessness of educational universities about accuracy of citation in thesis, not use of experts and specialized librarians for consultation, being not familiar with reference management software.
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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 | 0.020 | 0.161 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".