{"id":"W7098820720","doi":"","title":"Canadian Credit Aggregates Description Usage Format Details","year":2013,"lang":"en","type":"article","venue":"","topic":"Bioactive Natural Diterpenoids Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Credit history; Credit reference; Credit enhancement; Credit card interest; Variable (mathematics); Credit crunch; Installment credit; Credit score","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":[0.001489183,0.001947643,0.001283734,0.01051967,0.003172689,0.007252021,0.003409156,0.001184279,0.4383503],"category_scores_gemma":[0.01605861,0.001159632,0.0008683194,0.04061767,0.0005103185,0.004833932,0.001890447,0.00168076,0.274815],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01931514,"about_ca_system_score_gemma":0.02594639,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.875908,"about_ca_topic_score_gemma":0.8069814,"domain_scores_codex":[0.996536,0.0001367191,0.0003051567,0.0004320271,0.002112705,0.0004773765],"domain_scores_gemma":[0.976835,0.00104362,0.0006514993,0.001971772,0.01878226,0.0007159323],"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":[0.00002412757,0.000004645079,0.0004831724,0.00005991751,0.000003182348,0.0000098207,0.00002235291,0.0001085863,0.00003970614,0.001512528,0.9899563,0.007775748],"study_design_scores_gemma":[0.0000107234,0.000002412372,0.001907332,0.00004270957,0.000003910114,0.00001707493,0.00005751155,0.000152763,0.0001549281,0.000575296,0.9970521,0.00002317619],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.0002286099,0.0001149765,0.0007033614,0.0003212412,0.0001382839,0.0001014694,0.9489831,0.002175966,0.04723297],"genre_scores_gemma":[0.00284766,0.0006791608,0.002080064,0.0002598093,0.00007945174,0.0002496104,0.922213,0.002134173,0.06945707],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.4383503,"threshold_uncertainty_score":0.8011252,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01242755228917731,"score_gpt":0.2467025415257852,"score_spread":0.2342749892366079,"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."}}