Therapy‐associated effects in the prostate gland
Bibliographic record
Abstract
Diverse therapies are used to treat both benign prostatic hyperplasia and adenocarcinoma. Transurethral resection, a common surgical procedure, may give rise to characteristic necrobiotic granulomas that manifest in subsequent pathology samples. Radiation and hormone therapy have traditionally been used in prostatic adenocarcinoma. Morphological effects are often identified in needle biopsy specimens, transurethral resectates, and radical prostatectomy specimens. A range of histological changes are noted in the non-neoplastic prostate tissue, as well as in the pre-neoplastic and carcinomatous areas. Other ablative therapies, such as cryotherapy, and emerging focal therapies, including high-intensity focused ultrasound, photodynamic therapy, and interstitial laser thermotherapy, may have morphological effects on prostate tissue. It is important for the pathologist to be aware of the spectrum of histological changes affecting the prostate gland post-therapy. The treatment effects may obscure residual carcinoma, and make measurements of tumour extent and stage difficult. Furthermore, some therapies can profoundly alter the neoplastic glands to such an extent that Gleason scoring is no longer valid. As new therapies are developed for prostate cancer, it is important to document their effects on benign and malignant prostate tissue and to understand possible implications for traditional prognostic factors, especially Gleason grade.
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 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".