{"id":"W2914758922","doi":"10.3138/jcs.52.3.2017-0079.r1","title":"Federal-Provincial Variation in Leadership Selection: Processes and Participation","year":2018,"lang":"en","type":"article","venue":"Journal of Canadian Studies","topic":"Electoral Systems and Political Participation","field":"Social Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Legislature; Selection (genetic algorithm); Congruence (geometry); Convergence (economics); Public administration; Political science; Variation (astronomy); Federal election; Work (physics); Order (exchange); Politics; Economics; Economic growth; Law; Psychology; Social psychology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006269264,0.00004405532,0.0001203273,0.0002675664,0.0003411415,0.00005068093,0.00003226742,0.0000446831,0.00001892548],"category_scores_gemma":[0.00141349,0.00003914707,0.000012122,0.0005198768,0.0001351202,0.0002648041,0.000002678566,0.00006539122,0.000003337111],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002760068,"about_ca_system_score_gemma":0.000718464,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.2216675,"about_ca_topic_score_gemma":0.9816783,"domain_scores_codex":[0.9991924,0.0001278308,0.0002302955,0.00005553248,0.0001616113,0.0002323339],"domain_scores_gemma":[0.9990215,0.00009646428,0.000112761,0.00001670326,0.0005924031,0.0001601782],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001004368,0.00006306267,0.7861966,0.0002057912,0.0001497314,0.00001697669,0.1367693,0.00001779843,0.0004613119,0.05684303,0.01075023,0.00842563],"study_design_scores_gemma":[0.0005016549,0.000597291,0.9428326,0.0002011937,0.00004854052,0.000006907896,0.00961777,0.00003345347,0.0002556493,0.008847427,0.03685662,0.0002009015],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9832019,0.0006446555,0.00003858718,0.01319082,0.000321158,0.0001001864,9.110846e-7,0.000005175077,0.002496594],"genre_scores_gemma":[0.9983299,0.00003155239,0.00004712411,0.0002358281,0.001169263,0.000003740949,8.582649e-8,0.000002724188,0.0001797523],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7600108,"threshold_uncertainty_score":0.7835155,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1930144211155456,"score_gpt":0.3895074339423767,"score_spread":0.1964930128268311,"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."}}