JoVE Video Dataset
Bibliographic record
Abstract
Duodenal stenosis is a condition that can be related to several diseases, being either intrinsic, such as neoplasm and inflammatory stenosis, or extrinsic, such as pancreatic pseudocyst, superior mesenteric artery syndrome, and foreign bodies. Current treatments range from endoscopic approaches, such as endoscopic resection and stent placement, to surgical approaches, including duodenal resection, pancreaticoduodenectomy, and gastrointestinal bypass. Minimally invasive robot-assisted surgery is gaining importance due to its potential to decrease surgical stress, intraoperative blood loss, and postoperative pain, while its instruments and 3D-vision facilitate fine dissection and intra-abdominal suturing, all leading to a reduced time to functional recovery and shorter hospital stay. We present a case of a 75-year-old female who underwent robotic D3 partial duodenal resection with primary side-to-side duodeno-jejunal anastomosis for a 5 cm adenoma with focal high-grade dysplasia.
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 | 0.000 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.435 | 0.280 |
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".