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
BACKGROUND: The prevalence of undefined pancreatic cystic neoplasms (PCNs) is high in the general population, increasing with patient age. PCNs account for different biological entities with different potential for malignant transformation. The clinician must balance his or her practice between the risk of surgical overtreatment and the error of keeping a malignant lesion under surveillance. METHODS: We review and discuss the clinical management of PCNs. Specifically, we analyze the main features of PCNs from the surgeon's point of view, as they present in the outpatient clinic. We also review the different consensus guidelines, address recent controversies in the literature, and present the current clinical practice at 4 different European Centers for pancreatic surgery. RESULTS: The main features of PCNs were analyzed from the surgeon's point of view as they present in the outpatient clinic. All aspects of surgical management were discussed, from indications for surgery to intraoperative management and surveillance strategies. CONCLUSIONS: Management of PCNs requires a selective approach with the aim of minimizing clinically relevant diagnostic mistakes. Through the evaluation of clinical and radiological features of a PCN, the surgeon can elaborate on a diagnostic hypothesis and assess malignancy risk, but the final decision should be tailored to the individual patient's need.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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 | 0.001 |
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