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Record W2398667621

A guide to the management of urologic dilemmas for the primary care physician (PCP).

2014· article· en· W2398667621 on OpenAlexaff
Jack Barkin, Matt T. Rosenberg, Martin Miner

Bibliographic record

VenuePubMed · 2014
Typearticle
Languageen
FieldMedicine
TopicUrological Disorders and Treatments
Canadian institutionsHumber River Regional Hospital
Fundersnot available
KeywordsMedicineGuidelineRenal colicIntensive care medicinePrimary carePrimary care physicianIntervention (counseling)Emergency departmentUrologic diseaseWork-upUrinary systemMedical emergencySurgeryAlternative medicineNursingFamily medicineInternal medicinePathology
DOInot available

Abstract

fetched live from OpenAlex

Patients with urologic conditions may present to a primary care physician (PCP) in the emergency department or in the PCP's office. Some conditions are true emergencies that require immediate surgical intervention. Others may require medical treatment or possibly simply reassuring the patient that there is no serious medical problem. Sometimes the diagnosis can be easily made, whereas other times the PCP needs to be able to rule out serious causes for a presenting problem and execute a guideline-recommended patient work up, to make a final diagnosis. Sometimes recommended diagnostic tests may not be readily available. When a PCP believes that a patient may have a serious urologic condition and is unsure of the appropriate patient management strategy, then he or she must quickly refer the patient to a urologist. This article describes common urology-related issues-hematuria, prostate-specific antigen (PSA) test interpretation, phimosis and paraphimosis, acute scrotal pain and masses in the child and adult, urinary tract infection, renal colic, and castration-treatment-induced bone loss. It provides insights into decision-making processes for patient management of some urologic conditions, and information about managing sequelae and side effects of long term treatment. It includes practical diagnostic suggestions and patient management strategies based on the authors' years of urologic clinical practice experience.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.987
Threshold uncertainty score0.149

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 head0.242
Teacher spread0.221 · 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 designOther design
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

Citations4
Published2014
Admission routes1
Has abstractyes

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