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Record W2039277331 · doi:10.5489/cuaj.11179

The basic science behind overactive bladder: introduction

2011· article· en· W2039277331 on OpenAlexaffvenue
Jerzy B. Gajewski

Bibliographic record

VenueCanadian Urological Association Journal · 2011
Typearticle
Languageen
FieldMedicine
TopicUrinary Bladder and Prostate Research
Canadian institutionsDalhousie University
Fundersnot available
KeywordsOveractive bladderUrologyMedicineAlternative medicine

Abstract

fetched live from OpenAlex

The objective of this section of the supplement is to discuss the multifactorial pathophysiology of the overactive bladder syndrome (OAB) and translate this knowledge into the clinical environment. There are two separate articles on the pathophysiology, with Dr. Christopher Chapple focusing on the role of central neurogenic pathways and Dr. Pradeep Tyagi discussing the local pathways (neurogenic, myogenic and urothelial). The new look into this area of human bladder innervations brings new ideas of how to approach voiding dysfunction and particularly OAB. This is important to finding other mechanisms of intervention in OAB; exploring central nervous system (CNS) and specific neurogenic pathways opens up new areas of research and intervention. In recognition of the multiple pathways of bladder dysfunction, medical science has identified many potential targets for pharmacologic intervention. The third article of this section by Dr. Karl-Erik Andersson is devoted to research into the future pharmacological compounds to be tested in OAB. In the subsequent sections of this publication, clinical aspects of therapeutic efficacy of current and emerging treatment agents will be discussed in even greater detail.

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)0.001
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.003
Scholarly communication0.0020.004
Open science0.0010.001
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0100.004

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 head0.263
Teacher spread0.238 · 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 designNot applicable
Domainnot available
GenreEditorial

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
Published2011
Admission routes2
Has abstractyes

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