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Record W4213266926 · doi:10.1016/j.ekir.2022.01.574

POS-543 DO RENAL BIOPSIES ASSIST IN UNDERSTANDING OF LOIN PAIN HEMATURIA SYNDROME?

2022· article· en· W4213266926 on OpenAlexaff
Bhanu Prasad, Ashish Sharma, Mohammad Jafari, Pouneh Dokouhaki

Bibliographic record

VenueKidney International Reports · 2022
Typearticle
Languageen
FieldMedicine
TopicVascular anomalies and interventions
Canadian institutionsUniversity of SaskatchewanRegina General Hospital
Fundersnot available
KeywordsMedicineFlank painMicroscopic hematuriaPathophysiologyKidney diseaseGross hematuriaDiseaseKidneySurgeryPathologyInternal medicineProteinuria

Abstract

fetched live from OpenAlex

Loin pain-hematuria syndrome (LPHS) first described in 1967, is a complex and poorly understood rare disease that predominantly affects young women. Patients with LPHS experience extreme flank pain along with hematuria in the absence of a primary kidney pathology. Due to inadequate understanding of the pathophysiology of LPHS, the goal of management has been limited to symptomatic relief and pain management. While it is uncertain if the source of pain and hematuria are interrelated, there is consensus that hematuria is glomerular in origin.

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)0.002
metaresearch head score (Gemma)0.006
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 score0.008
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0080.004

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 head0.024
GPT teacher head0.277
Teacher spread0.253 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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