{"id":"W7131241487","doi":"10.25549/wpacards-ouc11579273","title":"WPA household census for 141 S TOWNSEND STREET, Los Angeles County","year":2021,"lang":"en","type":"dataset","venue":"University of Southern California Digital Library","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Census; Quarter (Canadian coin); Townsend; Data collection; Administration (probate law)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006741786,0.001189775,0.001094911,0.003205489,0.000586357,0.001930031,0.001401602,0.0005063943,0.07635452],"category_scores_gemma":[0.004167218,0.0005974752,0.0005187297,0.009486658,0.0001837432,0.00122192,0.0009423798,0.001478683,0.08043721],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001815333,"about_ca_system_score_gemma":0.003786877,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1305962,"about_ca_topic_score_gemma":0.1444033,"domain_scores_codex":[0.9991929,0.0001055461,0.0001177799,0.0002205158,0.0002646823,0.00009862999],"domain_scores_gemma":[0.9975876,0.000280327,0.0002335876,0.0002476022,0.001479537,0.0001714348],"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":[0.00000692791,0.000005834775,0.0007211077,0.00011512,0.000007192429,0.000006858791,0.00001223196,0.00004700401,0.00000778357,0.0002506002,0.9972811,0.00153818],"study_design_scores_gemma":[0.00006260297,0.000007221114,0.01696352,0.00031808,0.00001917984,0.00002966083,0.0001820722,0.0002083586,0.00006248993,0.0005245333,0.9816049,0.00001735336],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001228129,0.00005364547,0.00004317632,0.00004754117,0.00001588745,0.00001026335,0.9982565,0.00004548314,0.001404603],"genre_scores_gemma":[0.0005908315,0.0001615266,0.0001661958,0.00004142309,0.00001251515,0.0001152017,0.996146,0.00004040607,0.002725973],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9236455,"threshold_uncertainty_score":0.2596721,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01545785178870779,"score_gpt":0.1779223761285685,"score_spread":0.1624645243398607,"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."}}