Bibliographic record
Abstract
the 14th Annual Scientific Meeting as a hybrid congress in Istanbul, Turkey, October 05-08, 2023.Founded in 2003, the Balkan Academy of Forensic Sciences (BAFS) deals with all scientific, educational, and professional matters pertaining to the forensic nursing discipline on an international level.The primary goal of the Balkan Academy is to promote education for and research in the forensic sciences by encouraging the study to improve the practice, to elevate the standards and to advance the cause of the Forensic Sciences.Starting in 2021 the Balkan Academy endorsed a Forensic Nursing Section, in addition to 8 other preexisting sections.There are a very small number of NGOs in the Forensic Sciences arena with a Forensic Science Nursing Section.Therefore, we are proud to have the privilege of being one of the first institutions to undertake the responsibility to promote this science.We extend our gratitude to Virginia Lynch for her dedication and spirit.She organized the section and has been actively participating in the Annual Meetings for the last three years.The 2023 meeting hosted 275 attendees from 25 different countries and accepted 85 oral presentations and 50 posters in addition to two workshops and one panel.One of the most captivating sessions was the Forensic Nursing Session, and included presentations from scientists from USA, Canada, Switzerland Turkey, Portugal, Kosovo, and Iran on with topics such as:• Forensic Nurse Hospitalist:
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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 | 0.000 |
| 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".