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Record W4210985377 · doi:10.1097/mpa.0000000000001597

The North American Neuroendocrine Tumor Society Consensus Guidelines for Surveillance and Medical Management of Pancreatic Neuroendocrine Tumors

2020· article· en· W4210985377 on OpenAlexaff
Þorvarður R. Hálfdánarson, Jonathan Strosberg, Laura Tang, Andrew M. Bellizzi, Emily K. Bergsland, Thomas M. O’Dorisio, Daniel M. Halperin, Lauren Fishbein, Jennifer R. Eads, Thomas A. Hope, Simron Singh, Riad Salem, David C. Metz, Boris G. Naraev, Diane Reidy‐Lagunes, James R. Howe, Rodney F. Pommier, Yusuf Menda, Jennifer A. Chan

Bibliographic record

VenuePancreas · 2020
Typearticle
Languageen
FieldMedicine
TopicNeuroendocrine Tumor Research Advances
Canadian institutionsHealth Sciences CentreSunnybrook Health Science Centre
FundersNational Cancer Institute
KeywordsNeuroendocrine tumorsMedicinePanel discussionConsensus conferencePancreatic neuroendocrine tumorInternal medicineMEDLINEOncologyGeneral surgeryFamily medicinePolitical science

Abstract

fetched live from OpenAlex

Abstract This article is the result of the North American Neuroendocrine Tumor Society consensus conference on the medical management of pancreatic neuroendocrine tumors from July 19 to 20, 2018. The guidelines panel consisted of medical oncologists, pathologists, gastroenterologists, endocrinologists, and radiologists. The panel reviewed a series of questions regarding the medical management of patients with pancreatic neuroendocrine tumors as well as questions regarding surveillance after resection. The available literature was reviewed for each of the question and panel members voted on controversial topics, and the recommendations were included in a document circulated to all panel members for a final approval.

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 imitation

Not 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.

metaresearch head score (Codex)0.018
metaresearch head score (Gemma)0.039
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.018
Threshold uncertainty score0.096

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.039
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0070.004
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0030.002
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0050.004

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 head0.042
GPT teacher head0.344
Teacher spread0.301 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

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

Citations196
Published2020
Admission routes1
Has abstractyes

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