{"id":"W1670828499","doi":"10.24124/c677/2014497","title":"How to Win and Lose an Election: Campaign Dynamics of the 2011 Ontario Election","year":2014,"lang":"en","type":"article","venue":"Canadian Political Science Review","topic":"Canadian Identity and History","field":"Social Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wilfrid Laurier University","funders":"","keywords":"Salience (neuroscience); General election; Political science; Dynamics (music); Government (linguistics); Public administration; Federal election; Political economy; Advertising; Public relations; Economics; Business; Sociology; Law; Politics; Psychology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"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":[0.002214492,0.0002771507,0.0003928255,0.002248079,0.003933595,0.004637259,0.0006999933,0.0008983578,0.004892275],"category_scores_gemma":[0.009217467,0.0002285812,0.0002926027,0.005398073,0.002036916,0.001476736,0.0009298734,0.001152129,0.000674634],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05111397,"about_ca_system_score_gemma":0.06246715,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9581925,"about_ca_topic_score_gemma":0.990164,"domain_scores_codex":[0.9975901,0.0003692623,0.00009323796,0.000127676,0.0012048,0.0006149828],"domain_scores_gemma":[0.9952998,0.0009690116,0.0008510298,0.00008964794,0.002183535,0.0006069584],"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":[0.0004670829,0.00009619973,0.09126212,0.008353974,0.0003272852,0.0009275012,0.07256012,0.002170961,0.001521796,0.05585137,0.3489525,0.4175092],"study_design_scores_gemma":[0.00002177684,0.00003557972,0.27952,0.001521985,0.0001269181,0.00009312791,0.01769528,0.0002381663,0.0002110439,0.001301696,0.6991729,0.0000615096],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.2164294,0.4135146,0.0007768663,0.08173738,0.001768388,0.0001947125,0.004494985,0.00005288134,0.2810309],"genre_scores_gemma":[0.7099742,0.234067,0.0004614488,0.003863237,0.0007461173,0.00008243858,0.0020099,0.00007239473,0.04872327],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.948886,"threshold_uncertainty_score":0.3708596,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01240232724800099,"score_gpt":0.2493794557464302,"score_spread":0.2369771284984292,"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."}}