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Record W4283366043 · doi:10.7759/cureus.25819

Interpretation of Parathyroid Hormone Levels in Renal Impairment

2022· article· en· W4283366043 on OpenAlexaff
Ifeanyi F Nwosu, Cece E Ibeson, Adedoyin Olawoye, Htin Kyaw, Kelash Kumar, Celestine Odigwe, Chukwunonso A Nwosu, Anthony Oshunsanya

Bibliographic record

VenueCureus · 2022
Typearticle
Languageen
FieldMedicine
TopicParathyroid Disorders and Treatments
Canadian institutionsSt. Thomas Hospital
Fundersnot available
KeywordsMedicineParathyroid hormoneUrinalysisKidney diseaseMedical recordIntensive care medicineEmergency departmentMedical historyHormoneKidneyDiseaseInternal medicineUrologyUrineCalcium

Abstract

fetched live from OpenAlex

Distinguishing between acute kidney injury and chronic kidney disease (CKD) in an emergency setting may pose a conundrum for physicians, especially when a patient's medical history and records are unknown. Parathyroid hormone (PTH) has proved valuable as a marker of CKD and is frequently assayed for this reason. The use of PTH as a sole marker of CKD may be misleading in certain conditions, and for this reason, physicians need to interpret PTH values with caution. In patients with no existing medical records, it is vital to consider their overall clinical picture, an accurate interpretation of urinalysis and urine microscopy, and the PTH values when making the initial management decisions.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.832
Threshold uncertainty score0.274

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.020
GPT teacher head0.295
Teacher spread0.275 · 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

Citations9
Published2022
Admission routes1
Has abstractyes

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