{"id":"W6991554997","doi":"","title":"Identifying strong voter support : Condorcet and Smith revisited","year":2023,"lang":"en","type":"report","venue":"Dipòsit Digital de Documents de la UAB (Universitat Autònoma de Barcelona)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"Agencia Estatal de Investigación; Generalitat de Catalunya","keywords":"Condorcet method; Consistency (knowledge bases); Ridiculous; Population; Term (time); Selection (genetic algorithm)","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":[0.01106217,0.00053305,0.001889369,0.003609589,0.002710855,0.004724242,0.002323476,0.002975023,0.007984965],"category_scores_gemma":[0.05369508,0.0004866962,0.001250217,0.003605554,0.006343567,0.008958824,0.00331564,0.002590939,0.0006815487],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002999147,"about_ca_system_score_gemma":0.001424469,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002806217,"about_ca_topic_score_gemma":0.00240798,"domain_scores_codex":[0.992534,0.00344615,0.0003271496,0.001444127,0.001465818,0.0007826638],"domain_scores_gemma":[0.9742634,0.01489138,0.003515641,0.003552291,0.002750768,0.001026504],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001499641,0.00003020824,0.009447317,0.00007134627,0.00004689626,0.0001525861,0.001089688,0.002807185,0.0004024651,0.9492171,0.001487687,0.03509769],"study_design_scores_gemma":[0.00006393553,0.0001518163,0.006880716,0.00008978499,0.00006068133,0.0003063864,0.001294653,0.03332819,0.001304526,0.9474346,0.009028925,0.00005568984],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6393225,0.001667676,0.2533393,0.01100204,0.0001828557,0.0001982984,0.0004494908,0.0002142693,0.09362353],"genre_scores_gemma":[0.9824453,0.0001992053,0.0137061,0.0002734263,0.0001032415,0.00006628786,0.00006857179,0.00002728557,0.003110469],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01106217,"threshold_uncertainty_score":0.05850297,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04132872661311393,"score_gpt":0.3323766003640706,"score_spread":0.2910478737509567,"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."}}