{"id":"W6945552655","doi":"10.25549/wpacards-m24273","title":"WPA blocklist of household censuses for Woods, Vancouver Streets","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; Population; Work (physics); Poverty; Metropolitan area","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","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00009904043,0.0006619848,0.00101085,0.0005136356,0.000141054,0.00007310157,0.001397929,0.0005952439,0.001208604],"category_scores_gemma":[0.00006171762,0.0007193165,0.0006900344,0.0003666205,0.0007205859,0.0007356768,0.0008411064,0.0003635212,0.005368378],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007891928,"about_ca_system_score_gemma":0.000322995,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001753948,"about_ca_topic_score_gemma":0.00009986074,"domain_scores_codex":[0.9975298,0.00005814363,0.0005355004,0.0005889821,0.0006230937,0.0006644506],"domain_scores_gemma":[0.9970825,0.0002616708,0.001152995,0.001005263,0.0001110904,0.0003864756],"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":[0.0007995794,0.0006640372,0.002449929,0.0007495527,0.0003387618,0.00002672887,0.00002724302,0.00001653029,0.000009245648,0.000002769953,0.99472,0.0001956267],"study_design_scores_gemma":[0.001239721,0.0000794388,0.00001033302,0.0002973189,0.0004511378,0.000003191147,0.001407598,0.00000409502,0.00009963245,0.0001043229,0.995626,0.0006772427],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.002301649,0.0002152924,0.00001379028,0.00001673234,0.000138588,0.0005793651,0.9956452,0.0002257466,0.0008635822],"genre_scores_gemma":[0.002024188,0.00002770649,0.0003299325,0.00003023408,0.000208617,6.823401e-7,0.9962366,0.00021686,0.0009251652],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.004159774,"threshold_uncertainty_score":0.9997044,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01289970225047311,"score_gpt":0.1735802888231798,"score_spread":0.1606805865727067,"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."}}