MétaCan
Menu
Back to cohort
Record W1524159875 · doi:10.25011/cim.v33i1.11841

Survol du programme scientifique du congrès annuel de la SCRC-ACCFC 2009

2010· article· fr· W1524159875 on OpenAlexafffundvenueabout
Stephan Ong Tone, Sagar B. Dugani, Harry H. Marshall, Mohammed F. Shamji, Jean-Christophe Murray, Dominick Bossé

Bibliographic record

VenueClinical and investigative medicine · 2010
Typearticle
Languagefr
FieldMedicine
TopicHealth and Medical Research Impacts
Canadian institutionsUniversity of Ottawa
FundersInstitute of GeneticsCanadian Institutes of Health Research
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

Du 21 au 23 septembre 2009 a eu lieu à Ottawa le congrès annuel de l’Association des cliniciens-chercheurs en formation du Canada – Clinical Investigator Trainee Association of Canada (ACCFC-CITAC) et de la Société canadienne de recherche clinique (SCRC). Parmi les participants se trouvaient des cliniciens-chercheurs et des étudiants en provenance des quatre coins du pays. Cette conférence mettait à l’avant-plan des invités de marque, dont le récipiendaire actuel du Prix international de la recherche en santé Henry G. Friesen, Sir John Bell. Plusieurs tables rondes entourant le développement professionnel s’y tenaient, avec des sujets tels que « le support des cliniciens-chercheurs canadiens », « le succès des cliniciens-chercheurs » et « la collaboration internationale des MD+ en formation », tout en donnant l’opportunité d’établir des liens avec des mentors et collaborateurs potentiels. De plus, le congrès annuel de l’ACCFC-CITAC mettait en vedette plusieurs recherches impliquant des MD+ en formation à travers tout le Canada, dans le cadre de la séance de présentation par affiches du Forum des jeunes chercheurs ou lors de la séance plénière. Ce survol vise à mettre en évidence certaines des recherches présentées par les chercheurs en formation lors de la conférence annuelle, autant sur le plan de la recherche fondamentale que de la recherche clinique. Dans cet article, nous résumons les principales questions de recherche abordées par ces cliniciens-chercheurs en formation dans les disciplines suivantes: neurosciences, biologie cellulaire, médecine, immunologie, obstétrique, gynécologie, néonatalogie, orthopédie, rhumatologie et santé publique.

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)0.012
metaresearch head score (Gemma)0.021
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: Other · Consensus signal: Other
Teacher disagreement score0.132
Threshold uncertainty score0.441

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.021
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0020.001
Scholarly communication0.0050.002
Open science0.0030.005
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.1320.063

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 head0.427
GPT teacher head0.486
Teacher spread0.059 · 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
GenreOther

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

Citations1
Published2010
Admission routes4
Has abstractyes

Explore more

Same venueClinical and investigative medicineSame topicHealth and Medical Research ImpactsFrench-language works237,207