Current state of open access to journal publications from the University of Zagreb School of Medicine
Bibliographic record
Abstract
AIMS: To identify the share of open access (OA) papers in the total number of journal publications authored by the members of the University of Zagreb School of Medicine (UZSM) in 2014. METHODS: Bibliographic data on 543 UZSM papers published in 2014 were collected using PubMed advanced search strategies and manual data collection methods. The items that had "free full text" icons were considered as gold OA papers. Their OA availability was checked using the provided link to full-text. The rest of the UZSM papers were analyzed for potential green OA through self-archiving in institutional repository. Papers published by Croatian journals were particularly analyzed. RESULTS: Full texts of approximately 65% of all UZSM papers were freely available. Most of them were published in gold OA journals (55% of all UZSM papers or 85% of all UZSM OA papers). In the UZSM repository, there were additional 52 freely available authors' manuscripts from subscription-based journals (10% of all UZSM papers or 15% of all UZSM OA papers). CONCLUSION: The overall proportion of OA in our study is higher than in similar studies, but only half of gold OA papers are accessible via PubMed directly. The results of our study indicate that increased quality of metadata and linking of the bibliographic records to full texts could assure better visibility. Moreover, only a quarter of papers from subscription-based journals that allow self-archiving are deposited in the UZSM repository. We believe that UZSM should consider mandating all faculty members to deposit their publications in UZSM OA repository to increase visibility and improve access to its scientific output.
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 | 0.033 | 0.119 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.036 | 0.045 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.017 | 0.007 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.019 | 0.007 |
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".