Book Abstract: International Congress on health Science and Medical Technologies 2024
Bibliographic record
Abstract
International Congress on Health Sciences and Medical Technologies 2024: ICHSMT’24 is the 8th edition following several editions held online in 2021, and 2023 adding to in-person: Tlemcen, Algeria (2016, 2017, 2019 and 2022) and Algiers Algeria (2018). It is an annual congress containing several conferences and workshops focusing on Medical technologies and health sciences. The congress attracted researchers from several nations and specialties as: Algeria, Germany, Iran, Switzerland, Netherland, Denmark, Malaysia, Pakistan, France, Tunisia, Morocco, Brazil, Egypt, India, Iraq, Canada and Benin. The congress author’s affiliations were from several departments such as medicine, biology, physics and chemical sciences, computer sciences, veterinary, agronomy, environment, pharmacy, dental Medicine, electronic and mechanical engineering. The content was selected via strong criteria applied by the members of program committee. We received 127 submissions, which were reviewed by 1-5 reviewers and scanned by iThenticate software. We have accepted 91 abstracts presented in this book, the rate of acceptance was 71.75%.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.278 | 0.272 |
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".