{"id":"W6969383322","doi":"10.5683/sp3/klijlf","title":"Survey of Consumer Finances, 1978 [Canada]: Economic Family Income","year":2023,"lang":"en","type":"dataset","venue":"Borealis","topic":"Computational Physics and Python Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Statistics Canada","funders":"","keywords":"Microdata (statistics); Census; Spouse; Family income; Income distribution; Survey data collection; Household income; Survey of Income and Program Participation; Distribution (mathematics)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000252856,0.0001761565,0.0003199478,0.00009417635,0.00006457661,0.00005734808,0.001329734,0.00007641052,0.000003222915],"category_scores_gemma":[0.00002943112,0.0001886237,0.00005643551,0.0002926904,0.00004848188,0.00006801886,0.0003454104,0.0001377086,0.00009973579],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009768099,"about_ca_system_score_gemma":0.002004734,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9881768,"about_ca_topic_score_gemma":0.9679902,"domain_scores_codex":[0.9987414,0.00006707935,0.0003838484,0.0003821606,0.0002520279,0.0001734928],"domain_scores_gemma":[0.9979225,0.0005519133,0.000319022,0.001008085,0.0001270453,0.00007142754],"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":[0.000001006318,0.00001216902,0.00003598685,0.00002140582,0.00002708486,0.000002629552,0.000001833881,0.0002741376,1.825897e-7,0.004220821,0.9939963,0.001406501],"study_design_scores_gemma":[0.00007272965,0.000008780564,0.09628484,0.0000179274,0.000006747086,6.260779e-7,4.29331e-7,0.001360032,0.000001295256,0.001416998,0.9006538,0.0001757473],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00001750329,0.0001477041,0.0009391503,0.0001207787,0.000262538,0.0001386283,0.9981021,0.00002922777,0.0002423726],"genre_scores_gemma":[0.0002395717,0.0002345005,0.0002601402,0.0001517896,0.00004818593,0.00003546742,0.9989883,0.000008673545,0.00003332075],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09624885,"threshold_uncertainty_score":0.769185,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02840245640281886,"score_gpt":0.2684916184723702,"score_spread":0.2400891620695514,"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."}}