My approach to intraductal lesions of the prostate gland
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
The morphologically heterogeneous (intra)ductal lesions of the prostate frequently present a diagnostic challenge, particularly when found within prostate needle biopsies. By current convention, all high-grade intra-acinar and intraductal neoplastic lesions of prostatic origin fall under the diagnostic umbrella term: prostatic intraepithelial neoplasm (PIN). Although a long-standing contentious issue, some lesions currently adhering to the diagnostic criteria of PIN may actually represent the intraductal spread of (generally high grade) invasive cancer. Illustrating this fact, the well-described ductal subtype of prostatic adenocarcinoma is frequently associated with conventional-type acinar adenocarcinoma, and has a tendency to propagate within adjacent intact prostatic ducts. Clearly, the misdiagnosis of lesions representing invasive disease as preinvasive has the potential for unfavourable clinical sequelae. As yet, however, many of these lesions have escaped the establishment of reliable morphologic criteria or immunohistochemical differentiation for diagnosis. By defining stringent architectural and cytonuclear features specific for each of these lesions, it may be feasible to separate potentially sinister lesions from the subset of traditional (preinvasive) PIN lesions with limited clinical urgency. This review discusses the (intra)ductal lesions of the prostate, along with their differential diagnoses. Given the current state of knowledge, a pragmatic approach to their effective reporting is outlined, taking into consideration the clinical implications, as well as current guidelines for treatment and follow-up.
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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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