[Prostate specific antigen and diagnosis of prostate cancer].
Bibliographic record
Abstract
Prostate cancer had a development predominantly at peripheral gland and stay for a long time asymptomatic without clinical symptoms. When the cancer is symptomatic, it is often translate an advanced stage. The symptoms of prostate cancer are not specifics: urinary troubles, compression of iliac vessels or bone metastases pain. The digital rectal examination highlight an induration nodule, irregular and painless. The probability to have a cancer increase with the rate of the prostate specific antigen (PSA). Some others situations can increase the rate of PSA: benign prostatic hyperplasia, prostatitis, bladder catheterisation, urinary retention, endoscopic examination. The ratio of free-PSA/total-PSA (fPSA/tPSA) permits a best discrimination between benign prostatic hyperplasia and prostate cancer The more fPSA/tPSA ratio is low, the more the risk of prostate cancer is high. Prostate cancer is suspected with the digital rectal examination and the rate of PSA but the diagnosis is made by histological examination (the tissue samples are took by transrectal ultrasound-guided biopsies). The staging of disease must be realised according to the risk of metastasis appreciated by clinical stage, rate of PSA and Gleason score.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.032 | 0.017 |
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".