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The management of intraductal papillary mucinous neoplasms of the pancreas

2019· review· en· W2992441041 on OpenAlexaff
Tommaso Pollini, Stefano Andrianello, Andrea Caravati, Giampaolo Perri, Giuseppe Malleo, Salvatore Paiella, Giovanni Marchegiani, Roberto Salvia

Bibliographic record

VenueMinerva Chirurgica · 2019
Typereview
Languageen
FieldMedicine
TopicPancreatic and Hepatic Oncology Research
Canadian institutionsPancreas Centre (Canada)
Fundersnot available
KeywordsMedicinePancreasIntraductal papillary mucinous neoplasmGeneral surgeryPancreatic ductRadiologyInternal medicine

Abstract

fetched live from OpenAlex

Intraductal papillary mucinous neoplasms (IPMN) of the pancreas are one of the most common preneoplastic entities among pancreatic cystic neoplasms (PCN). Their incidence is increasing due to an extensive use of cross-sectional imaging, but management still remains controversial. Among IPMNs, the main duct (MD-IPMN) and mixed (MT-IPMN) types harbor a high risk of malignant degeneration requiring resection in most of cases. The branch duct type (BD-IPMN), on the other side, can be safely surveilled as surgical resection is limited to selected cases deemed at high risk of malignant progression according to specific clinical and radiological features. An accurate diagnosis and a correct assessment of malignant potential are often hard to achieve, and clinical management still relies on the experience of the gastroenterologist/surgeon that is called to choose between a major pancreatic resection burdened by high morbidity and mortality rates and a life-long surveillance. The purpose of this report is to summarize the available evidence supporting the current practice for the management of IPMN and to offer a useful practical guide from first observation to postoperative 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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.972
Threshold uncertainty score0.625

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.057
GPT teacher head0.358
Teacher spread0.300 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations8
Published2019
Admission routes1
Has abstractyes

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