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Record W2769816443 · doi:10.4236/mri.2017.64004

Nephrotic Sydrome Can Be a Marker for Prostatic Carcinoma

2017· article· en· W2769816443 on OpenAlexfundno aff
Natasha Takova, Alexander Otsetov

Bibliographic record

VenueModern Research in Inflammation · 2017
Typearticle
Languageen
FieldMedicine
TopicRenal Diseases and Glomerulopathies
Canadian institutionsnot available
FundersCancerforskningsfonden i NorrlandCentre Hospitalier Universitaire de Québec
KeywordsNephrotic syndromeMedicineGlomerulopathyCarcinomaAsymptomaticEtiologyOccultCancerMembranoproliferative glomerulonephritisRenal cell carcinomaPathologyInternal medicineGlomerulonephritisOncologyKidney

Abstract

fetched live from OpenAlex

Paraneoplastic syndromes (PS) represent a large spectrum of symptoms, associated with malignant diseases. PS can be diagnosed in asymptomatic patients with occult carcinoma, clinically active cancer, and during clinical remission, suggesting a recurrence of the neoplasm. The underlying mechanisms of PS are not completely understood but several authors have suggested that the increased production of biologically active immune factors and cytokines from the neoplastic cells may underlie the etiology of PS. Although rare, the renal involvement of patients with prostatic carcinoma has been reported. The most common paraneoplastic-associated glomerulopathy in prostatic cancer is the membranoproliferative glomerulonephritis with nephrotic syndrome (NS). In this review, we aimed to discuss the incidence of nephrotic syndrome secondary to prostatic carcinoma, its challenging diagnosis, clinical manifestation, and treatment.

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)0.001
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: none
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.109
GPT teacher head0.397
Teacher spread0.288 · 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
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueModern Research in Inflammation→Same topicRenal Diseases and Glomerulopathies→French-language works237,207→