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Record W2413281140 · doi:10.1097/mpa.0000000000000620

Future Directions in the Treatment of Gastrointestinal and Pancreatic Neuroendocrine Tumors

2016· article· en· W2413281140 on OpenAlexaff
Timothy R. Asmis

Bibliographic record

VenuePancreas · 2016
Typearticle
Languageen
FieldMedicine
TopicNeuroendocrine Tumor Research Advances
Canadian institutionsOttawa Hospital
Fundersnot available
KeywordsNeuroendocrine tumorsMedicineClinical trialIntensive care medicineDiseaseGeneral surgeryInternal medicine

Abstract

fetched live from OpenAlex

Recently, the landscape of the diagnosis and treatment of patients with well-differentiated gastrointestinal/pancreatic neuroendocrine tumors (previously referred to as carcinoid tumors) has changed dramatically. We will need to work with all of the stakeholders including clinicians, patients, regulatory agencies, and industry to best navigate future treatment and research. Future protocols will require us to define clinically relevant end points. In designing future clinical trials, we will need to determine which patients will be included in these studies. Future research will need to address the best way to image and follow patient's disease both in the clinic and on research studies. Timely access to new therapies will be the utmost importance to both current and future patients. We must work together to establish relevant clinical questions and to pursue collaborative research that promotes the health of our patients.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.059
Threshold uncertainty score0.263

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.018
GPT teacher head0.297
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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations2
Published2016
Admission routes1
Has abstractyes

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