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Record W3030505602 · doi:10.1097/jp9.0000000000000004

A Chinese consensus statement on the diagnosis and treatment of pancreatic exocrine insufficiency after pancreatic surgery (2018)

2018· article· en· W3030505602 on OpenAlexaff
Taiping Zhang, Zhe Cao, Rufu Chen, Yiqi Du, Defei Hong, Kuirong Jiang, Gang Jin, Fei Li, Weiqin Li, Zhao‐Shen Li, Tingbo Liang, Quan Liao, Wenhui Lou, Yi Miao, Jiaming Qian, Renyi Qin, Bei Sun, Zhaohui Tang, Chunyou Wang, Weilin Wang, Wenming Wu, Yinmo Yang, Gang Zhao, Yupei Zhao

Bibliographic record

VenueJournal of Pancreatology · 2018
Typearticle
Languageen
FieldMedicine
TopicPancreatitis Pathology and Treatment
Canadian institutionsPancreas Centre (Canada)
Fundersnot available
KeywordsStatement (logic)Exocrine pancreatic insufficiencyConsensus conferenceMedicineGeneral surgeryChinaEpidemiologyTherapeutic approachIntensive care medicineSurgeryInternal medicinePolitical sciencePancreatitisPhilosophyEpistemology

Abstract

fetched live from OpenAlex

Abstract A consensus statement on the diagnosis and treatment of pancreatic exocrine insufficiency (PEI) after pancreatic surgery was developed based on the latest references, combined with China's actual situation. More than 20 Chinese excellent experts participated in this work and contributed many thorough discussions. This consensus discusses the definition, epidemiology, diagnosis, treatment, and follow-up of PEI after pancreatic surgery. The authors hope this consensus will promote the standard procedure of diagnosis and treatment of PEI in China.

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)0.053
metaresearch head score (Gemma)0.067
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: Other · Consensus signal: none
Teacher disagreement score0.053
Threshold uncertainty score0.278

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0530.067
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.005
Bibliometrics0.0070.004
Science and technology studies0.0020.002
Scholarly communication0.0030.002
Open science0.0050.004
Research integrity0.0070.008
Insufficient payload (model declined to judge)0.0040.002

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 head0.033
GPT teacher head0.312
Teacher spread0.279 · 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
GenreOther

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

Citations1
Published2018
Admission routes1
Has abstractyes

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