The Second Asia-Oceania Human Proteome Organization (AOHUPO) Online Education Series on the Renaissance of Clinical Proteomics: Biomarkers, Imaging and Therapeutics
Bibliographic record
Abstract
In 2021, the Asia-Oceania Human Proteome Organization (AOHUPO) initiated a new endeavor named the AOHUPO Online Education Series with the aim to promote scientific education and collaboration, exchange of ideas and culture among the young scientists in the AO region. Following the warm participation, the AOHUPO organized the second series in 2022, with the theme "The Renaissance of Clinical Proteomics: Biomarkers, Imaging and Therapeutics". This time, the second AOHUPO Online Education Series was hosted by the UKM Medical Molecular Biology Institute (UMBI) affiliated to the National University of Malaysia (UKM) in Kuala Lumpur, Malaysia on three consecutive Fridays (11th, 18th and 25th of March). More than 300 participants coming from 29 countries/regions registered for this 3-days event. This event provided an amalgamation of six prominent speakers and all participants whose interests lay mainly in applying MS-based and non-MS-based proteomics for clinical investigation.
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.105 | 0.024 |
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".