{"id":"W2783767745","doi":"","title":"Fourth annual workshop on data-driven knowledge mobilization.","year":2017,"lang":"en","type":"article","venue":"Conference of the Centre for Advanced Studies on Collaborative Research","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta; University of Toronto; Queen's University","funders":"","keywords":"Mobilization; Computer science; Data science; Knowledge management; Political science","routes":{"ca_aff":true,"ca_fund":false,"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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.01509386,0.001267683,0.001400068,0.002632157,0.00139475,0.0114722,0.004463881,0.00349479,0.0460758],"category_scores_gemma":[0.02024903,0.0008554795,0.001534067,0.002349517,0.00259328,0.01403594,0.007986699,0.004031331,0.01276858],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002741088,"about_ca_system_score_gemma":0.00489104,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004444551,"about_ca_topic_score_gemma":0.005760659,"domain_scores_codex":[0.9945695,0.002453848,0.0003378014,0.0008828467,0.00130237,0.0004535698],"domain_scores_gemma":[0.985232,0.006309228,0.0002551148,0.003591098,0.003030726,0.001581775],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0007242652,0.0005454954,0.00143105,0.0009028898,0.0001679368,0.0003901254,0.002580498,0.002706673,0.003798742,0.1269644,0.361047,0.4987409],"study_design_scores_gemma":[0.00007342835,0.0001047257,0.001118242,0.0007864002,0.00008969626,0.0003245566,0.001589653,0.009685534,0.00516155,0.1137426,0.8672587,0.00006493522],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.0200748,0.04125651,0.6426237,0.07685637,0.02060966,0.0009093694,0.004330276,0.00556524,0.187774],"genre_scores_gemma":[0.1930279,0.02033976,0.4888853,0.007980182,0.004350118,0.0010577,0.01699786,0.00260574,0.2647554],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.9849061,"threshold_uncertainty_score":0.1541389,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2861860519477305,"score_gpt":0.4756191753746572,"score_spread":0.1894331234269267,"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."}}