{"id":"W4285803296","doi":"10.1093/ijpp/riac054","title":"Lessons learned from using whiteboard videos and YouTube for deprescribing guidelines knowledge mobilization","year":2022,"lang":"en","type":"article","venue":"International Journal of Pharmacy Practice","topic":"Health Literacy and Information Accessibility","field":"Health Professions","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Trillium Health Centre; University of British Columbia; McGill University; Queen's University; Bruyère; University of Ottawa","funders":"Centre d’innovation canadien sur la santé du cerveau et le vieillissement","keywords":"Library science; Whiteboard; Medicine; Media studies; Sociology; World Wide Web; Computer science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02344345,0.001336948,0.0005466544,0.002619791,0.002400166,0.006845,0.002770508,0.002370554,0.009418047],"category_scores_gemma":[0.06082057,0.0004532604,0.001113837,0.001196756,0.002616331,0.01045411,0.006790949,0.003190788,0.00231775],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002552689,"about_ca_system_score_gemma":0.003501633,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005898658,"about_ca_topic_score_gemma":0.01622319,"domain_scores_codex":[0.9770379,0.01783966,0.0006775947,0.000840225,0.002169831,0.001434683],"domain_scores_gemma":[0.9533742,0.03493567,0.001143738,0.001831289,0.004805217,0.003909857],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.0002381003,0.002387298,0.009926471,0.00326598,0.0000708811,0.001975975,0.07124001,0.0006718418,0.001872924,0.003577437,0.1159682,0.7888048],"study_design_scores_gemma":[0.0006495357,0.004837756,0.03139979,0.01934431,0.0002486052,0.004028501,0.277177,0.006791416,0.007713133,0.01765112,0.62967,0.0004888957],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5185776,0.01653201,0.09140133,0.1822382,0.006743219,0.0110085,0.00302723,0.005205397,0.1652665],"genre_scores_gemma":[0.7217647,0.01857229,0.198121,0.0207294,0.002214508,0.007065042,0.002931026,0.001351723,0.02725023],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02344345,"threshold_uncertainty_score":0.1239823,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.508133317518578,"score_gpt":0.6189542338918752,"score_spread":0.1108209163732972,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}