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Record W4406352689 · doi:10.1016/s2213-8587(24)00308-5

Outcomes after medical treatment for primary aldosteronism: an international consensus and analysis of treatment response in an international cohort

2025· article· en· W4406352689 on OpenAlexaff
Jun Yang, Jacopo Burrello, Jessica Goi, Martín Reincke, Christian Adolf, Evelyn Asbach, Denise Brüdgam, Qifu Li, Ying Song, Jinbo Hu, Shumin Yang, Fumitoshi Satoh, Yoshikiyo Ono, Renata Libianto, Michael Stowasser, Nanfang Li, Qing Zhu, Namki Hong, Troy Puar, Vin‐Cent Wu, Anand Vaidya, Marta Araujo‐Castro, Tomaž Kocjan, Samuel O’Toole, Gregory L. Hundemer, Óskar Ragnarsson, André Lacroix, Stéphanie Larose, Kazuki Nakai, Tetsuo Nishikawa, D. O. Ladygina, Adina F. Turcu, Julieta Sholinyan, Carlos Fardella, Thomas Uslar, Marcus Quinkler, Paolo Mulatero, Giovanni Pintus, Gian Paolo Rossi, Stefanie Hahner, Laurence Amar, William M Drake, Chetna Varsani, Morris J. Brown, Xi‐Lin Wu, Jaap Deinum, E. Marie Freel, Gregory Kline, Mitsuhide Naruse, Aleksander Prejbisz, William F. Young, Tracy Ann Williams, Peter J. Fuller

Bibliographic record

VenueThe Lancet Diabetes & Endocrinology · 2025
Typearticle
Languageen
FieldMedicine
TopicHormonal Regulation and Hypertension
Canadian institutionsUniversity of CalgaryCentre Hospitalier de l’Université de MontréalUniversity of Ottawa
FundersAgencia Nacional de Investigación y DesarrolloPontificia Universidad Católica de ChileNational Health and Medical Research CouncilHudson Institute of Medical ResearchNational Heart, Lung, and Blood InstituteState Government of VictoriaNational Institute on AgingAgenția Națională pentru Cercetare și DezvoltareMinistry of Health, Labour and WelfareDeutsche ForschungsgemeinschaftNational Institute for Health and Care ResearchHudson Institute
KeywordsMedicinePrimary aldosteronismCohortMEDLINECohort studyIntensive care medicineInternal medicineAldosterone

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 score0.028
Threshold uncertainty score0.333

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 head0.035
GPT teacher head0.354
Teacher spread0.319 · 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

Citations54
Published2025
Admission routes1
Has abstractno

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