{"id":"W7131307658","doi":"10.25549/wpacards-c8-151278","title":"WPA household census for 6715 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); Data collection; American Community Survey; Administration (probate law); Value (mathematics)","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":[0.0006539016,0.001191635,0.001040199,0.00304108,0.0005637457,0.001828728,0.001331709,0.000511103,0.07401726],"category_scores_gemma":[0.004027754,0.0005686287,0.0005210827,0.008385039,0.0001824101,0.001194925,0.0009152366,0.00140756,0.08772393],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001810538,"about_ca_system_score_gemma":0.003518704,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1315701,"about_ca_topic_score_gemma":0.1483498,"domain_scores_codex":[0.9992384,0.00009974197,0.00009888973,0.0002242966,0.0002477378,0.0000909612],"domain_scores_gemma":[0.9976846,0.0002690139,0.0002285882,0.0002430509,0.0014189,0.0001558164],"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":[0.000006923502,0.000005432361,0.000755761,0.00009728287,0.000006868889,0.000006183772,0.00001060256,0.00004546604,0.000007149527,0.000209317,0.9973464,0.001502622],"study_design_scores_gemma":[0.00006666435,0.000006763365,0.01488112,0.0002984588,0.00001917244,0.00002785344,0.0001697663,0.0002273836,0.00006766776,0.0004792013,0.9837399,0.00001605709],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001292506,0.00005101098,0.00004332079,0.00004885043,0.00001405232,0.000007880805,0.998503,0.00004666856,0.001156069],"genre_scores_gemma":[0.0005473625,0.0001269557,0.0001374194,0.00003596193,0.00001047792,0.00009103519,0.9964773,0.00003433456,0.002539167],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1315701,"threshold_uncertainty_score":0.2616085,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01581263156476309,"score_gpt":0.1755721020672777,"score_spread":0.1597594705025146,"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."}}