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Record W2910611591 · doi:10.1016/s2213-8587(18)30336-x

Natural history, treatment, and long-term follow up of patients with multiple endocrine neoplasia type 2B: an international, multicentre, retrospective study

2019· article· en· W2910611591 on OpenAlexaff
Frédéric Castinetti, Steven G. Waguespack, Andreas Machens, Shinya Uchino, Kornelia Hasse-Lazar, Gabriella Sanso, Tobias Else, Šárka Dvořáková, Xiao Ping Qi, Rossella Elisei, John Glod, Delmar Muniz Lourenço, Nuria Valdés, Jes Sloth Mathiesen, Nelson Wohllk, Tushar Bandgar, D. Drui, Márta Korbonits, Maralyn Druce, Caroline Brain, Tom Kurzawinski, Attila Patócs, Maria João Bugalho, André Lacroix, Philippe Caron, Patricia Day, Françoise Borson‐Chazot, Marc Klein, Thera P. Links, Claudio Letizia, Laura Fugazzola, Olivier Chabre, Letizia Canu, R. Cohen, Antoine Tabarin, Anita Špehar Uroić, Dominique Maiter, Sandrine Laboureau, Caterina Mian, Mariola Pęczkowska, Frederic Sebag, Thierry Brue, Delphine Mirebeau‐Prunier, Laurence Leclerc, Birke Bausch, A. Berdelou, Akihiro Sukurai, Petr Vlček, Jolanta Krajewska, Marta Barontini, Carla Vaz Ferreira Vargas, Laura Valerio, Lucieli Ceolin, Srivandana Akshintala, Ana O. Hoff, Christian Godballe, Barbara Jarząb, Camilo Jiménez, Charis Eng, Tsuneo Imai, Martin Schlumberger, Elizabeth G. Grubbs, Henning Dralle, Hartmut P.H. Neumann, Éric Baudin

Bibliographic record

VenueThe Lancet Diabetes & Endocrinology · 2019
Typearticle
Languageen
FieldMedicine
TopicThyroid Cancer Diagnosis and Treatment
Canadian institutionsCentre Hospitalier de l’Université de Montréal
FundersNational Cancer InstituteNational Institutes of HealthRosetrees Trust
KeywordsMedicineNatural historyTerm (time)Retrospective cohort studyEndocrine systemIntensive care medicineMEDLINEPediatricsOncologyInternal medicineHormone

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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 score0.023
Threshold uncertainty score0.601

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.270
Teacher spread0.252 · 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

Citations149
Published2019
Admission routes1
Has abstractno

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