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Record W2013105840 · doi:10.1159/000167502

Renal Potassium Handling during States of Low Aldosterone Bio-Activity: A Method to Differentiate Renal and Non-Renal Causes

2008· article· en· W2013105840 on OpenAlexaff
Randy M. Zettle, Michael L. West, Robert G. Josse, Robert Richardson, Philip A. Marsden, Mitchell L. Halperin

Bibliographic record

VenueAmerican Journal of Nephrology · 2008
Typearticle
Languageen
FieldMedicine
TopicHormonal Regulation and Hypertension
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsAldosteroneMedicineMineralocorticoidEndocrinologyInternal medicineHyperkalemiaNephronKidneyPotassiumRenal physiologyHormoneChemistry

Abstract

fetched live from OpenAlex

The purpose of this study was to examine renal potassium handling in patients with low aldosterone bio-activity. The patients with a normal renal response to aldosterone were identified by finding both a low plasma aldosterone concentration during hyperkalaemia and a transtubular potassium concentration gradient (TTKG) in the cortical distal nephron of 6 or greater within 4 h after the administration of a physiologic dose of mineralocorticoid hormone. In contrast, patients with a primary renal potassium excretion defect represent a heterogeneous population. In some, the TTKG rose when a pharmacologic but not a physiologic dose of mineralocorticoid was given; others had little renal response to the administration of this hormone. Furthermore, this renal response may be delayed and require more than 24 h to become manifest.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.283
Teacher spread0.265 · 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 source (direct Gemma or distilled Codex), 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

Citations48
Published2008
Admission routes1
Has abstractyes

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