{"id":"W7131290523","doi":"10.25549/wpacards-ouc11579436","title":"WPA household census for 127 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00009276812,0.000759222,0.0009670984,0.0004100922,0.0002453511,0.0002877562,0.00130122,0.0006670908,0.0002358397],"category_scores_gemma":[0.0000767112,0.0008546993,0.000728704,0.0004673017,0.0005842845,0.0006416566,0.0009192777,0.0005045162,0.0006224998],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001478218,"about_ca_system_score_gemma":0.0005507797,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001799213,"about_ca_topic_score_gemma":0.0001259394,"domain_scores_codex":[0.9971147,0.00008181891,0.0004653749,0.0009397707,0.0007049199,0.0006934068],"domain_scores_gemma":[0.997402,0.0002861392,0.0006949062,0.001071314,0.0001312268,0.0004144126],"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":[0.0005772891,0.000435466,0.0008804451,0.0005972432,0.0002988999,0.0004113815,0.000004019433,0.00001798345,0.000007804309,0.000002970721,0.9965761,0.0001904095],"study_design_scores_gemma":[0.001132386,0.00004633486,0.000008951799,0.0003637726,0.000356758,0.00001424384,0.001920055,0.00001493779,0.00004952548,0.00009530786,0.9951491,0.0008486553],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001546144,0.0003478047,0.00001267394,0.00004335543,0.00008747728,0.0005362044,0.9964189,0.0003477167,0.0006597388],"genre_scores_gemma":[0.0001085396,0.00004637164,0.0002604126,0.00008692917,0.0002616988,9.178505e-7,0.9984837,0.000234933,0.0005165564],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.002064756,"threshold_uncertainty_score":0.9993904,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01554096084551638,"score_gpt":0.1778232809674061,"score_spread":0.1622823201218897,"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."}}