{"id":"W6927025648","doi":"10.25549/wpacards-m82887","title":"WPA block face card for household census of Olympic, Colby, Federal Streets, in Los Angeles County","year":2012,"lang":"en","type":"dataset","venue":"University of Southern California Digital Library","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Census; Block (permutation group theory); Quarter (Canadian coin); Face (sociological concept)","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":[],"consensus_categories":[],"category_scores_codex":[0.0004943176,0.001546762,0.00123687,0.0051375,0.0007483506,0.001819316,0.001938057,0.0009592747,0.1107236],"category_scores_gemma":[0.003820438,0.0008787782,0.0006527002,0.01127172,0.0002145686,0.001147202,0.001162926,0.001271736,0.1182678],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001675292,"about_ca_system_score_gemma":0.003767272,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1783149,"about_ca_topic_score_gemma":0.2409413,"domain_scores_codex":[0.9993305,0.00005281048,0.0000870485,0.0001789212,0.0002154804,0.0001351995],"domain_scores_gemma":[0.9973434,0.0002572808,0.0003906544,0.0003385248,0.00139686,0.0002733417],"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":[0.00002462909,0.00001286176,0.001320311,0.0001094773,0.000009206829,0.000008151192,0.00001516899,0.00008551573,0.00002381669,0.0001177215,0.9967873,0.001485863],"study_design_scores_gemma":[0.0001819223,0.00001730573,0.04517566,0.0002591963,0.00003480529,0.00004423445,0.0002731814,0.0005161355,0.0003603701,0.0003986635,0.9526975,0.00004107367],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000145622,0.00001020369,0.00002687293,0.00001373077,0.000006267476,0.000009455154,0.9990565,0.00006275739,0.0006685988],"genre_scores_gemma":[0.0004682759,0.00002742657,0.00009453783,0.00001687272,0.000005465931,0.0000948522,0.9968784,0.00002724139,0.002386911],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1783149,"threshold_uncertainty_score":0.3704072,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0149503076412913,"score_gpt":0.1817521637751728,"score_spread":0.1668018561338815,"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."}}