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Record W2334358572 · doi:10.1097/mpa.0000000000000549

Inaugural Meeting of North American Pancreatic Cancer Organizations

2015· article· en· W2334358572 on OpenAlexaboutno aff
Barbara Kenner, Julie Fleshman, Ann Goldberg, Laura J. Rothschild

Bibliographic record

VenuePancreas · 2015
Typearticle
Languageen
FieldMedicine
TopicPancreatic and Hepatic Oncology Research
Canadian institutionsnot available
FundersSky FoundationCaring for Carcinoid FoundationCelgeneHirshberg Foundation for Pancreatic Cancer ResearchNational Pancreas FoundationPancreatic Cancer Action Network
KeywordsPancreatic cancerMedicineCancerGeneral surgeryPolitical scienceInternal medicine

Abstract

fetched live from OpenAlex

A meeting of North American Pancreatic Cancer Organizations planned by Kenner Family Research Fund and Pancreatic Cancer Action Network was held on July 15-16, 2015, in New York City. The meeting was attended by 32 individuals from 20 nonprofit groups from the United States and Canada. The objectives of this inaugural convening were to share mission goals and initiatives, engage as leaders, cultivate potential partnerships, and increase participation in World Pancreatic Cancer Day. The program was designed to provide opportunities for informal conversations, as well as facilitated discussions to meet the stated objectives. At the conclusion of the meeting, the group agreed that enhancing collaboration and communication will result in a more unified approach within the field and will benefit individuals diagnosed with pancreatic cancer. As a first step, the group will actively collaborate to participate in World Pancreatic Cancer Day, which is planned for November 13, 2015, and seeks to raise the level of visibility about the disease globally.

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)0.008
metaresearch head score (Gemma)0.006
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 score0.033
Threshold uncertainty score0.110

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0060.001
Scholarly communication0.0050.002
Open science0.0010.005
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0330.009

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 head0.037
GPT teacher head0.347
Teacher spread0.311 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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