{"id":"W2169202192","doi":"10.2139/ssrn.1118163","title":"Executive Control and Legislative Success","year":2009,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Judicial and Constitutional Studies","field":"Social Sciences","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Legislature; Control (management); Psychology; Business; Political science; Computer science; Artificial intelligence; Law","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":[],"consensus_categories":[],"category_scores_codex":[0.006698433,0.0002703165,0.0004987652,0.0026884,0.003551841,0.006756369,0.0007164003,0.002150028,0.01812033],"category_scores_gemma":[0.02698816,0.000244574,0.0002760637,0.002348951,0.004385094,0.002607645,0.002104451,0.002910863,0.001261566],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001332715,"about_ca_system_score_gemma":0.002305369,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006322552,"about_ca_topic_score_gemma":0.01212065,"domain_scores_codex":[0.9966196,0.001246073,0.0001119075,0.0002307245,0.0004966402,0.001295049],"domain_scores_gemma":[0.9582188,0.02313279,0.008120817,0.001233351,0.00244658,0.00684772],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008704281,0.001467046,0.7112496,0.00007898925,0.0002088733,0.001063327,0.01823321,0.001046566,0.0005684667,0.2242381,0.008005966,0.03296945],"study_design_scores_gemma":[0.0002303161,0.000471455,0.8323665,0.0001623824,0.0001729952,0.0004191512,0.04268348,0.002311914,0.0009303419,0.09180436,0.02838283,0.00006419687],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8873587,0.00111925,0.0001737044,0.006393726,0.00004254224,0.00001568299,0.00008265413,0.00001205414,0.1048018],"genre_scores_gemma":[0.9964619,0.0001205267,0.00001424471,0.0001438234,0.00004258805,0.000004898787,0.00002384221,0.000003114149,0.003184914],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01812033,"threshold_uncertainty_score":0.06061852,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009194659230791389,"score_gpt":0.2776136947112972,"score_spread":0.2684190354805058,"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."}}