The third symposium on treatment-induced neuroendocrine prostate cancer: insights and future directions
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Neuroendocrine prostate cancer (NEPC) is a rare and aggressive subtype of prostate cancer (PCa), emerging from advanced treatments and characterized by loss of androgen receptor (AR) signaling and neuroendocrine features, leading to rapid progression and treatment resistance. The third symposium on treatment-induced NEPC, held from 21 to 23 June 2024, at Harrison Hot Springs Resort, BC, Canada, united leading global researchers and clinicians. Sponsored by the Vancouver Prostate Centre (VPC), Canadian Institute of Health Research, Prostate Cancer Foundation Canada and Pharma Planter Inc, the event focused on the latest NEPC research and innovative treatment strategies. Co-chaired by Drs. Yuzhuo Wang and Martin Gleave, the symposium featured sessions on NEPC's historical context, molecular pathways, epigenetic regulation and the role of the tumor microenvironment and metabolism in its progression. Keynotes from experts like Dr. Himisha Beltran and Dr. Martin Gleave highlighted the complexity of NEPC. The Emerging Talent session showcased new research, pointing to the future of NEPC treatment. The symposium concluded with a consensus on the need for early detection, targeted therapies and personalized medicine to effectively combat NEPC, emphasizing the importance of global collaboration in advancing NEPC understanding and treatment.
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.
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 it