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Record W2063879601 · doi:10.1159/000182221

Acidosis and Renal Calcium Excretion in Experimental Chronic Renal Failure

2008· article· en· W2063879601 on OpenAlexaff
Claudio Marone, Norman L.M. Wong, Roger A.L. Sutton, John H. Dirks

Bibliographic record

Venue˜The œNephron journals/Nephron journals · 2008
Typearticle
Languageen
FieldMedicine
TopicRenal function and acid-base balance
Canadian institutionsUniversity of British Columbia
FundersMedical Research CouncilSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
KeywordsMedicineInternal medicineMetabolic acidosisEndocrinologyAzotemiaAcidosisCalciumExcretionRenal functionRenal tubular acidosisRenal physiologyCalcium metabolismUremia

Abstract

fetched live from OpenAlex

In renal failure, absolute calcium excretion is low, but fractional excretion (FE) of filtered load is increased. In order to determine the role of metabolic acidosis in contributing to increased FECa, we have studied thyroparathyroidectomized dogs in a control phase and following the induction of chronic renal failure, both during spontaneous metabolic acidosis and after correction with NaHCO3. FECa was 3.7% in controls and increased to 13.7% in azotemic acidotic dogs (p less than 0.01). After correction of acidosis FENa was not significantly changed, but FECa fell significantly, to 8.1% (p less than 0.01), while glomerular filtration rate, plasma calcium and filtered calcium load were unchanged. Thus although FECa is increased in nonacidotic azotemic dogs, acidosis further enhances calcium excretion by inhibiting renal tubular calcium reabsorption. These effects of metabolic acidosis may contribute to hypocalcemia and bone disease in azotemia.

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 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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.556
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.036
GPT teacher head0.305
Teacher spread0.270 · 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.

Study designBench or experimental
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

Citations13
Published2008
Admission routes1
Has abstractyes

Explore more

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