{"id":"W7131223854","doi":"10.25549/wpacards-ouc11572829","title":"WPA household census for 6716 CHANSLOR AVE, 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); American Community Survey; Data collection; Administration (probate law); Population; Variety (cybernetics)","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":[0.0006536181,0.001205117,0.001039494,0.003085978,0.0005630017,0.001835855,0.0013288,0.0005114031,0.07453765],"category_scores_gemma":[0.004056401,0.0005684813,0.0005279213,0.008435024,0.0001837741,0.001200563,0.0009210715,0.001419822,0.08881234],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001798468,"about_ca_system_score_gemma":0.00350841,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1301362,"about_ca_topic_score_gemma":0.1462873,"domain_scores_codex":[0.9992378,0.0001001384,0.00009938063,0.0002241242,0.0002476863,0.0000910125],"domain_scores_gemma":[0.9977102,0.0002653151,0.0002286189,0.0002450565,0.001395904,0.0001548299],"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":[0.000006961161,0.000005367648,0.0007540493,0.00009720783,0.000006969583,0.000006218035,0.00001044982,0.00004608725,0.000007112606,0.0002094991,0.9973368,0.001513338],"study_design_scores_gemma":[0.00006551007,0.000006631684,0.01453707,0.0002957693,0.00001903338,0.00002791098,0.0001649981,0.0002258082,0.00006716947,0.0004795513,0.9840947,0.000015938],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001269084,0.00005135387,0.00004342025,0.00004873176,0.00001412467,0.000007727334,0.9985113,0.00004758247,0.001148917],"genre_scores_gemma":[0.0005394045,0.0001271765,0.0001371556,0.00003513385,0.00001055439,0.0000891204,0.9964806,0.00003480067,0.002545901],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9254624,"threshold_uncertainty_score":0.2587574,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01543049140615445,"score_gpt":0.1750041836566255,"score_spread":0.159573692250471,"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."}}