The 6th Albanian Congress of Trauma and Emergency Surgery
Bibliographic record
Abstract
After a three-year quarantine from the deadliest global pandemic of the last century, ASTES is organizing to gather all health professionals in Tirana, The 6th Albanian Congress of Trauma and Emergency Surgery(ACTES 2022) on 11-12 November 2022, with the topic Trauma & Emergency Surgery and not only...with the aim of providing high quality, the best standards, and the best results, for our patients ...ACTES 2022 is the largest event that ASTES (Albanian Society for Trauma and Emergency Surgery) has organized so far with 230 presentations, and 67 foreign lecturers with enviable geography, making it the largest national and wider scientific event.The scientific program is as strong as ever, thanks to the inclusiveness, where all the participants with a mix of foreign and local lecturers, select the best of the moment in medical science, innovation, and observation.The scientific committee has selected all the presentations so that the participants of each medical discipline will have something to learn, discuss, debate, and agree with updated methods, techniques, and protocols.I hope you will join us on Friday morning, and continue the journey of our two-day event together.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.064 | 0.016 |
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".