Evaluation of Compliance Abstracts of Persian-language Journals Tehran University of Medical Sciences with ISO 214 & Vancouver's Group Guideline , in 2009
Bibliographic record
Abstract
Background and Aim: Homogeneity and Oneness is the feature of abstracting. These can't be achieved, without adherence to guidelines and international standards. The purpose of this study is evaluation of compliance abstracts of Persian-language journals of Tehran University of Medical Sciences, with ISO 214 & Vancouver's group guideline, in year 2009.Materials and Methods: Survey-descriptive method was adapted. The study sample included all full-text journal Reviews in English Persian language belonging to Tehran University of Medical Sciences. These journals were significant in TUMS website to date (30/2/2009). Total 100 abstracts from the latest issue of the journal articles for instance, were randomly selected. The data collected through two control lists separately, reflecting the standards of ISO 214 and instructions group in Vancouver for abstract writing. The data were analyzed by software and statistical techniques.Results: The average overall rate of compliance with ISO standards Review is 85/37 percent (SD 24/93 percent), and group instructions Vancouver is 84/44 percent (SD 24/36). Review of the "express findings" had the most and the "sub results presented" had minimum compliance with ISO standards. The "keyword existence" and "noted the findings" had the most and the "being derived from the headings keywords subject had "minimum compliance with the instructions in Vancouver group.Discussion and Conclusion:. The abstract compliance with ISO 214 and Vancouver instruction was desirable. More comply from ISO 214 in "results presented" and Vancouver group instruction in, keywords subject in medicine seems to be required.
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 | 0.068 | 0.237 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".