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Record W4318995034 · doi:10.1503/cjs.014021

Organizing a virtual scientific conference: experiences from the Bethune Round Table 2021

2023· article· en· W4318995034 on OpenAlexaffvenueabout
Rajan Bola, Tarek Razek, Dan Deckelbaum, Dolores Cviticanin, Ronald Lett

Bibliographic record

VenueCanadian Journal of Surgery · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicConferences and Exhibitions Management
Canadian institutionsMcGill University Health Centre
Fundersnot available
KeywordsMedicineRound tableCoronavirus disease 2019 (COVID-19)Library scienceTable (database)Pandemic2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Medical educationWorld Wide WebPathologyDisease

Abstract

fetched live from OpenAlex

In response to the COVID-19 pandemic, organizations used virtual platforms to host academic meetings. This includes the Canadian Network for International Surgery and the Centre for Global Surgery at the McGill University Health Centre, who were tasked with organizing the Bethune Round Table (BRT), held May 28-31, 2021. With 496 registrants and 300 attendees representing 50 countries, the BRT 2021 was the most trafficked BRT conference in its 20-year history. One month after the conference's conclusion, attendees were continuing to view the recorded sessions. Here we describe the successes of the virtual BRT 2021 conference and the plan to continue offering a digital mode of delivery for future BRT conferences.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.259
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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 head0.098
GPT teacher head0.279
Teacher spread0.181 · 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.

Study designNot applicable
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

Citations2
Published2023
Admission routes3
Has abstractyes

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