UPDATE – 2022 Canadian Urological Association recommendations on prostate cancer screening and early diagnosis: Endorsement of the 2021 Cancer Care Ontario guidelines on prostate multiparametric magnetic resonance imaging
Bibliographic record
Abstract
Guideline: PSA screening and early diagnosis that were published between January 1, 2016 and February 2, 2017.To identify articles not yet indexed, a search was also performed using PubMed without MEDLINE filters (see Appendix 1 for search strategy).For the fifth question related to additional diagnostic tests beyond PSA, which can potentially aid in the early detection of prostate cancer, a systematic search was performed in a similar fashion with no date restriction for tests not covered by existing guidelines.Case series, case reports, non-systematic reviews, editorials, and letters to the editor were excluded and the search strategy was restricted to English language articles.Trained methodologists implemented the specific search strategy and two authors reviewed the titles and abstracts of potential studies to identify their relevance for full-text review.Levels of evidence and grades of recommendation are provided according to the International Consultation on Urologic Diseases modification of the 2009 Oxford Centre for Evidence-Based Medicine grading system. 2
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 | 0.011 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.007 | 0.003 |
| Research integrity | 0.014 | 0.013 |
| Insufficient payload (model declined to judge) | 0.022 | 0.010 |
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".