Canadian Rheumatology Association Meeting Virtual Congress February 24 – 26, 2021
Bibliographic record
Abstract
The 75th Annual Meeting of The Canadian Rheumatology Association was held virtually on February 24-26, 2021. The program consisted of presentations covering original research, symposia, awards, and lectures. Highlights of the meeting include the following 2021 Award Winners: Distinguished Rheumatologist, Rachel Shupak; Distinguished Investigator, Sasha Bernatsky; Distinguished Teacher-Educator, Elaine Yacyshyn; Emerging Investigator, Zahi Touma; Ian Watson Award for the Best Abstract on SLE Research by a Trainee, Raffaella Carlomagno; Phil Rosen Award for the Best Abstract on Clinical or Epidemiology Research by a Trainee, Kimberley Yuen; Best Abstract by a Rheumatology Resident, Ariane Barbacki; Best Abstract on Basic Science Research by a Trainee, Andrew Kwan; Best Abstract by a Post-Graduate Research Trainee, Luiza Grazziotin; Best Abstract on Quality Care Initiatives in Rheumatology, Nadia Luca; Best Abstract by a Medical Student, Daniel Levin; Best Abstract by an Undergraduate Student, Anson Lee; Best Abstract by a Rheumatology Post-Graduate Research Trainee, Jennifer Lee; Best Abstract on Research by Young Faculty, Lihi Eder; Best Abstract on Spondyloarthritis Research, Sandeep Dhillon; Practice Reflection Award, Gold, Stephanie Gottheil; CRA Master Awards, Ciarán M. Duffy, Mary-Ann Fitzcharles, James M. Henderson. Lectures and other events included: Keynote Lecture by Danielle Martin: Delivering on What Matters: Lessons from Canada’s Response to the COVID-19 Pandemic; State of the Art Lecture by Michael Libman: Vaccination and Travel: Should I or Shouldn’t I?; Dunlop-Dottridge Lecture by Dan Kastner: Rheumatic Disease and the Human Condition; and the Great Debate: Be it Resolved that Telemedicine Allows Rheumatologists to Provide Excellent Care to Patients with Autoimmune Rheumatic Diseases. Arguing for: Alexandra Saltman and Tommy Gerschman, and against: Brent Ohata and Jocelyne Murdoch. Topics including rheumatoid arthritis, systemic lupus erythematosus, systemic sclerosis, Sjögren syndrome, psoriatic arthritis, spondyloarthritis, vasculitis, osteoarthritis, fibromyalgia, and their respective diagnoses, treatments, and outcomes are reflected in the abstracts, which we are pleased to publish in this issue of The Journal .
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".