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Record W4404995876 · doi:10.1245/s10434-024-16591-0

Outcomes for Patients with Obesity Undergoing Adrenalectomy for Pheochromocytoma: An International Multicenter Analysis

2024· article· en· W4404995876 on OpenAlexaff
Kevin Verhoeff, Alessandro Parente, Yanbo Wang, Nanya Wang, Zhicheng Wang, Maciej Śledziński, Andrzej Hellmann, Marco Raffaelli, Francesco Pennestrì, Mark Sywak, Alexander Papachristos, Fausto Palazzo, Tae‐Yon Sung, Byung-Chang Kim, Yu‐Mi Lee, Fiona Eatock, Hannah Anderson, Maurizio Iacobone, Albertas Daukša, Özer Makay, Yiğit Türk, Hafize Basut Atalay, Els J. M. Nieveen van Dijkum, Anton F. Engelsman, Isabelle Holscher, Gabriele Materazzi, Leonardo Rossi, Chiara Becucci, Susannah Shore, Clare Fung, Alison Waghorn, Radu Mihai, Sabapathy P. Balasubramanian, Arslan Pannu, Shuichi Tatarano, David Velázquez‐Fernández, Julie Ann Miller, Hazel Serrao‐Brown, Yufei Chen, Marco Stefano Demarchi, Reza Djafarrian, H Doran, Kelvin Wang, Michael Stechman, Helen Perry, Johnathan Hubbard, Cristina Lamas, Philippa Mercer, Janet L. Macpherson, Supanut Lumbiganon, María Calatayud, Felicia A. Hanzu, Óscar Vidal, Marta Araujo-Castro, C. Mínguez Ojeda, Theodossis S. Papavramidis, Pablo Rodríguez de Vera Gómez, Abdulaziz Aldrees, Tariq Altwjry, Nuria Valdés, Cristina Álvarez‐Escolá, Íñigo García Sanz, Concepción Blanco Carrera, Laura Manjón, Paz de Miguel Novoa, Mónica Recasens, Rogelio García Centeno, Cristina Robles Lázaro, Klaas Van Den Heede, Sam Van Slycke, Theodora Michalopoulou, Sebastian Aspinall, Ross Melvin, Joel Wen Liang Lau, Wei Keat Cheah, Man Hon Tang, Han Boon Oh, John Ayuk, Robert P. Sutcliffe

Bibliographic record

VenueAnnals of Surgical Oncology · 2024
Typearticle
Languageen
FieldMedicine
TopicAdrenal and Paraganglionic Tumors
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineAdrenalectomyBody mass indexObesityPheochromocytomaSurgical oncologyInternal medicineComplicationUrologySurgery

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 score0.183
Threshold uncertainty score0.365

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 head0.045
GPT teacher head0.389
Teacher spread0.344 · 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

Citations7
Published2024
Admission routes1
Has abstractno

Explore more

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