Bibliographic record
Abstract
The Serican Academy of Urology (SAU), established in the fall of 2022, is an international non-profit organization dedicated to uniting clinicians and basic scientists to address diseases related to the genitourinary tract. Prostate cancer, particularly castration-resistant prostate cancer (CRPC), remains a significant public health issue. The second annual SAU conference was held from June 13-16, 2024, at Banff Rocky Mountain Resorts, Alberta, Canada. Sponsored by MedChemExpress, ABclonal, and NovinoPath, and chaired by Dr. Xiaoqi Liu, the conference focused on the latest research in urological diseases. Topics included epigenetic regulation, novel treatment targets, bioinformatics, cancer etiology, progression and metastasis, the tumor microenvironment and immunotherapy, and overcoming resistance to existing therapies. Keynote addresses by leading scientists Drs. Jindan Yu and Qianben Wang emphasized the complexity of epigenetic and transcriptional regulation in prostate cancer. The Women’s Forum provided a platform to discuss career navigation and leadership development for women scientists in a predominantly male field. The conference concluded with a banquet, including an awards ceremony and committee reports.
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 | 0.008 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.055 | 0.022 |
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".