Intraoperative Consultation and Macroscopic Handling
Bibliographic record
Abstract
The International Society of Urological Pathology held a conference on issues in testicular and penile pathology in Boston in March 2015, which included a presentation by the testis macroscopic features working group. The presentation focused on current published guidance for macroscopic handling of testicular tumors and retroperitoneal lymph node dissections with a summary of results from an online survey of members preceding the conference. The survey results were used to initiate discussions, but decisions on practice were made by expert consensus rather than voting. The importance of comprehensive assessment at the time of gross dissection with confirmation of findings by microscopic assessment was underscored. For example, the anatomic landmarks denoting the distinction of hilar soft tissue invasion (pT2) from spermatic cord invasion (pT3 category) can only be determined by careful macroscopic assessment in many cases. Other recommendations were to routinely sample epididymis, rete testis, hilar soft tissue, and tunica vaginalis in order to confirm macroscopic invasion of these structures or if not macroscopically evident, to exclude subtle microscopic invasion. Tumors 2 cm or less in greatest dimension should be completely embedded. If the tumor is >2 cm in greatest dimension, 10 blocks or a minimum of 1 to 2 additional blocks per centimeter should be taken (whichever is greater).
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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.034 | 0.008 |
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".