{"id":"W6913183637","doi":"10.5683/sp2/7q0xl9","title":"Replication Data for: Voter Turnout and Income Inequality in Canada and the Indian States","year":2021,"lang":"en","type":"dataset","venue":"Borealis","topic":"","field":"","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Gini coefficient; Voter turnout; Economic inequality; Inequality; Panel data; Income distribution; Replication (statistics); Macro; Time series","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":["metaresearch"],"domain":"reproducibility","study_design":"not_applicable","genre":"dataset","about_ca_system":false,"about_ca_topic":true,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":[],"domain":null,"study_design":"not_applicable","genre":"dataset","about_ca_system":false,"about_ca_topic":true,"confidence":"high","status":"direct model label, unvalidated"}],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001034005,0.001159274,0.0009427238,0.003512638,0.002362978,0.002461442,0.003172022,0.001034769,0.02589564],"category_scores_gemma":[0.007004011,0.0005169442,0.0008937764,0.008972484,0.0006081084,0.0006018009,0.001345475,0.001633895,0.01418197],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01126565,"about_ca_system_score_gemma":0.02612526,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9663031,"about_ca_topic_score_gemma":0.9783084,"domain_scores_codex":[0.9988723,0.00007906372,0.00006271269,0.0001642732,0.0004736141,0.0003479341],"domain_scores_gemma":[0.9938405,0.0003468681,0.0004220912,0.0006831851,0.004096027,0.0006112793],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001149196,0.00004102651,0.008621784,0.0001688461,0.00005577839,0.0000519826,0.0000950243,0.0006994266,0.00008030686,0.0008330754,0.9857023,0.003535432],"study_design_scores_gemma":[0.0004217677,0.0000274216,0.146036,0.0003085698,0.00008381835,0.0001051366,0.0007441625,0.001920275,0.0008437345,0.0008009387,0.8485898,0.0001183339],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001542314,0.00005134748,0.00004460942,0.0001260439,0.00001911257,0.00002692368,0.9969723,0.0001313813,0.001085897],"genre_scores_gemma":[0.004701894,0.00005446234,0.0002605232,0.00005399801,0.000009830974,0.0001008371,0.99186,0.00003789613,0.002920646],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03369695,"threshold_uncertainty_score":0.08662951,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03081318710190172,"score_gpt":0.2970932207270087,"score_spread":0.2662800336251069,"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."}}