MétaCan
Menu
Back to cohort
Record W1901898645 · doi:10.5489/cuaj.795

Quantifying CUA’s progress

2013· article· en· W1901898645 on OpenAlexaffvenue
Jerzy B. Gajewski

Bibliographic record

VenueCanadian Urological Association Journal · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBiomedical Text Mining and Ontologies
Canadian institutionsCanadian Urological Association
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

A s CUA President, I am pleased to be able to report on some updates stemming from the CUA Strategic Plan.We have established 7 task forces to meet the goals set out in the Plan. 1. Develop and implement an education business plan that will meet the life-long needs of members and contribute to overall CUA revenue 2. Develop and implement an advocacy business plan that will position the CUA as the voice of matters urological in Canada 3. Develop and implement a publishing business plan that will support the CUA's education and advocacy initiatives and contribute to overall CUA revenue 4. Develop and implement a practice support business plan that will be of value to the membership 5. Develop and implement a member engagement/value strategy 6. Develop a sustainable funding base, working with current partners to identify a broader range of revenue options 7. Design and implement the appropriate organizational model We have delineated a timeline for each of these 7 items.Chairs and members have been selected.The updates were presented at Winter Executive Meeting with the plan to present the first-year progress to CUA members at Annual General Meeting this summer in Charlottetown on Tuesday, June 26 at noon.On a related note, the results of our 2009 survey have been released.This data will help us understand the needs of our members and will allow us to develop a more valuable benefit package.As the data suggests (see Fig. 1), the patient brochures and the CUA Annual Meeting tie as the most valuable benefits for members.Close in second is our journal, CUAJ.These results are encouraging and helpful in knowing that CUA is on the right track in its services to members.Another recent CUA initiative contributing to improving societal health is the urologic information site -uroinfo.ca(www.uroinfo.ca).This site is becoming the "go-to" place for patients.The information on this site is written by CUA members.The goal of the site is to be the source of honest and balanced information about urology.The site is open to the general public, patients and their family members.The CUA Executive is continuing to restructure the Central Office with the goal of using our resources more effectively and efficiently.We will keep you informed on changes as they happen -stay tuned to the CUA Newsletter and the CUAJ for any updates.We will continue to do our best to serve our members.We welcome your feedback!I encourage you to attend our Annual General Meeting and to get involved in the association -your association!Let me end this report by inviting you to join us in Charlottetown for our first-ever Annual Meeting in Prince Edward Island!Dr. Michael Mulligan and Ian Reid, along with the rest of the local organizing committee, have been working hard to make sure that every attendee will enjoy the social program.The scientific program, chaired by Dr. Ricardo Rendon, will feature state-of the-art lectures from key opinion leaders in urology, educational fora addressing a wide spectrum of the most compelling issues and controversies in urology, and abstract-driven session showcasing the most cutting-edge research being done in Canada today.For more information and to register online, visit www.cuameeting.org.

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)0.007
metaresearch head score (Gemma)0.044
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 score0.054
Threshold uncertainty score0.107

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.044
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0130.010
Science and technology studies0.0020.001
Scholarly communication0.0060.006
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.021
GPT teacher head0.256
Teacher spread0.235 · 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
Published2013
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Urological Association JournalSame topicBiomedical Text Mining and OntologiesFrench-language works237,207