{"id":"W3184805219","doi":"","title":"Getting out the vote: raising involvement in Vancouver's 2018 Election","year":2018,"lang":"en","type":"article","venue":"UVic’s Research and Learning Repository (University of Victoria)","topic":"Labor Movements and Unions","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Raising (metalworking); Spoilt vote; Political science; Voting; Group voting ticket; Law; Engineering; Politics","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":[0.003108157,0.0002581169,0.0002903601,0.001045118,0.01985586,0.005005924,0.001284112,0.001681933,0.01651126],"category_scores_gemma":[0.009806343,0.0004085976,0.0001580644,0.001017672,0.00197064,0.001316021,0.005109023,0.004526698,0.002679536],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01325773,"about_ca_system_score_gemma":0.01844462,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5486906,"about_ca_topic_score_gemma":0.8823324,"domain_scores_codex":[0.9966514,0.0009879543,0.0000600718,0.0001586831,0.0005936043,0.001548278],"domain_scores_gemma":[0.9883968,0.001233097,0.0003494586,0.0001895373,0.001985187,0.007845866],"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":[0.0004178299,0.001355607,0.1470003,0.0002676979,0.00003032922,0.001780207,0.2817158,0.0001721664,0.001709601,0.006445664,0.2480995,0.3110053],"study_design_scores_gemma":[0.00008668833,0.0003083478,0.1660117,0.000443088,0.00003199669,0.0002313256,0.422715,0.0003746156,0.0007113689,0.001531159,0.4074918,0.00006277565],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8047516,0.0005446282,0.0004967781,0.03179364,0.0007868598,0.0002931987,0.0002903197,0.00011499,0.160928],"genre_scores_gemma":[0.8936925,0.0006311163,0.0007036195,0.003853333,0.0001267087,0.0002195119,0.0003245094,0.00006711484,0.1003816],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4513094,"threshold_uncertainty_score":0.9079345,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03349970518162956,"score_gpt":0.3035371058898079,"score_spread":0.2700374007081783,"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."}}