{"id":"W4398886649","doi":"10.7910/dvn/qtoiqf/rnjj7f","title":"figures_d1_to_d3.R","year":2019,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Race, History, and American Society","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Legitimation; Publicity; Replication (statistics); Political science; Public opinion; Law; Biology","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001327352,0.002609574,0.002080836,0.005473678,0.001075159,0.004371612,0.003935338,0.00223125,0.3935229],"category_scores_gemma":[0.01482987,0.0009453151,0.001537293,0.00954038,0.0006677458,0.002442164,0.003040307,0.002077679,0.3420576],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001811218,"about_ca_system_score_gemma":0.002702042,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02541955,"about_ca_topic_score_gemma":0.04078936,"domain_scores_codex":[0.9988543,0.0002122688,0.0001249432,0.0003617855,0.0002394486,0.0002073117],"domain_scores_gemma":[0.9955809,0.00155418,0.0003950929,0.001003697,0.0009358963,0.0005301953],"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":[0.00001851757,0.000006237138,0.0002645498,0.000348533,0.00001736586,0.000005369022,0.0000103854,0.00008676591,0.00002022539,0.0004284417,0.9979823,0.0008112485],"study_design_scores_gemma":[0.0002037188,0.000008433654,0.001525112,0.0004074612,0.00003154973,0.00002336111,0.00004486324,0.0002039771,0.0001515779,0.002154564,0.9952189,0.00002638896],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"software","genre_scores_codex":[0.00002403541,0.00003878217,0.00003591539,0.00005853007,0.00002106687,0.000004372884,0.9988163,0.0002919432,0.0007090205],"genre_scores_gemma":[0.0003595104,0.0000878634,0.0002303265,0.000105139,0.00001851574,0.00008573684,0.9974316,0.0003042216,0.001377064],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.606477,"threshold_uncertainty_score":0.8650659,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02313507796900203,"score_gpt":0.2886779275984669,"score_spread":0.2655428496294648,"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."}}