{"id":"W4293167525","doi":"10.2196/preprints.31827","title":"Using a Virtual Community of Practice to Support Stroke Best Practice Implementation: Mixed Methods Evaluation (Preprint)","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Stroke Rehabilitation and Recovery","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Thematic analysis; Best practice; Focus group; Community of practice; Knowledge translation; Analytics; Knowledge sharing; Qualitative research; Knowledge management; Computer science; Psychology; Data science; Business; Sociology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.130826,0.001637158,0.002699204,0.003251668,0.003701078,0.005926761,0.002556969,0.002767131,0.007394567],"category_scores_gemma":[0.1116685,0.001636929,0.003744545,0.003383597,0.00243262,0.00360131,0.005129702,0.001792105,0.001011133],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01109298,"about_ca_system_score_gemma":0.03676089,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006588517,"about_ca_topic_score_gemma":0.01125506,"domain_scores_codex":[0.8677781,0.1047465,0.01200174,0.003361528,0.008308342,0.003803851],"domain_scores_gemma":[0.8964123,0.06187951,0.007951017,0.006926487,0.02213638,0.004694416],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.02982801,0.0496562,0.02037564,0.03750859,0.002704898,0.0004135584,0.04810451,0.001937109,0.001825723,0.004230703,0.007217098,0.796198],"study_design_scores_gemma":[0.1493256,0.3924039,0.1058668,0.09109722,0.01168169,0.0005148836,0.1161315,0.006197946,0.01507198,0.008083322,0.1025098,0.001115446],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5501708,0.004984439,0.01404064,0.002008827,0.0007944517,0.4133293,0.002509951,0.0003396193,0.01182191],"genre_scores_gemma":[0.3702263,0.002462224,0.06123741,0.001673179,0.0002122489,0.5608349,0.0007607793,0.00008909764,0.002503865],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.130826,"threshold_uncertainty_score":0.691882,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1668806399774513,"score_gpt":0.5433311626175555,"score_spread":0.3764505226401043,"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."}}