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Record W2029658908 · doi:10.1097/mpa.0b013e3181ec1380

NANETS Consensus Guideline for the Diagnosis and Management of Neuroendocrine Tumors

2010· article· en· W2029658908 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePancreas · 2010
Typearticle
Languageen
FieldMedicine
TopicNeuroendocrine Tumor Research Advances
Canadian institutionsLondon Health Sciences Centre
Fundersnot available
KeywordsMedicineNeuroendocrine tumorsGuidelineForegutDiseaseThorax (insect anatomy)EpidemiologyInternal medicineIncidence (geometry)PathologyIntensive care medicineOncology

Abstract

fetched live from OpenAlex

Neuroendocrine tumors (NETs) of the thorax, including bronchial and thymic neuroendocrine NETs, are often referred to as NETs of the foregut. The incidence and prevalence of NETs are increasing in the United States as demonstrated in the Surveillance, Epidemiology, and End Results from 1973 to 2004 (J Clin Oncol. 2008;26[18]:3063-3072). Although the majority of bronchial and thymic NETs are sporadic, approximately 5% to 10% can be associated with hereditary syndrome, multiple endocrine neoplasms type 1 (Nat Rev Cancer. 2005;5[5]:367-375). Diagnosis is made by tissue pathology, allowing for characterization and classification of the NET. Radiologic evaluation is performed to determine the extent of disease involvement. Clinical symptoms from hormonal overproduction or from paraneoplastic processes are medically managed to improve patients' quality of life. Locoregional disease can be curative with surgery; however, distant or metastatic disease is rarely curable. Therapeutic options for metastatic/advanced NETs of the thorax are mainly to palliate symptoms. Final treatment recommendations for patients with either bronchial or thymic NETs should be individualized, weighing the risks and benefits of therapy.

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.

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)0.001
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.560
Threshold uncertainty score0.356

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.031
GPT teacher head0.346
Teacher spread0.315 · 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