{"id":"W7101133142","doi":"","title":"DOMESTIC FINANCIAL STATISTICS","year":2005,"lang":"en","type":"article","venue":"","topic":"SAS software applications and methods","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Section (typography); Statistical analysis; Year-ending; Numbering; Business statistics; Economic statistics; Quarter (Canadian coin)","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":[0.005591136,0.001027794,0.001209984,0.01992419,0.000913676,0.004700763,0.001167249,0.000908671,0.1789247],"category_scores_gemma":[0.0504366,0.0005917295,0.0006417157,0.0248244,0.0005167355,0.002654705,0.00145992,0.002191634,0.1553987],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002991394,"about_ca_system_score_gemma":0.004877653,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01106247,"about_ca_topic_score_gemma":0.008630651,"domain_scores_codex":[0.9899107,0.001342462,0.001467787,0.0009588189,0.005747627,0.0005726005],"domain_scores_gemma":[0.9576488,0.008686366,0.006015699,0.004032797,0.02217609,0.001440287],"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":[0.00003086764,0.0000140096,0.001881542,0.0001489061,0.000009559604,0.0000168316,0.00005441289,0.0001273377,0.00003406656,0.004337408,0.9608455,0.03249952],"study_design_scores_gemma":[0.00001131564,0.00001833885,0.007492785,0.000175509,0.000008657652,0.00008224028,0.00008795001,0.0002971003,0.0001208229,0.00194679,0.9897413,0.00001722489],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.003534767,0.003648879,0.005270694,0.00383375,0.001694539,0.0005277104,0.7443646,0.003845541,0.2332796],"genre_scores_gemma":[0.02481959,0.006877179,0.0074143,0.001250815,0.001594785,0.001065103,0.7937863,0.001738796,0.1614531],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1789247,"threshold_uncertainty_score":0.5985629,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00921928963602937,"score_gpt":0.2736645065366898,"score_spread":0.2644452169006604,"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."}}