{"id":"W7116068572","doi":"10.5683/sp3/fbvj4k","title":"National Input-Output Tables, North American Industry Classification System (NAICS), 1962-2005 [Canada]","year":2025,"lang":"","type":"dataset","venue":"Borealis","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Identification (biology); Government (linguistics); Feature (linguistics); Work (physics)","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":[0.00113384,0.003126232,0.002114185,0.007453274,0.001634173,0.003258241,0.004245607,0.001544552,0.04475201],"category_scores_gemma":[0.007266656,0.000924106,0.001971224,0.01813489,0.0007191614,0.001443262,0.001445548,0.002747996,0.04906943],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01422124,"about_ca_system_score_gemma":0.03563929,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9031634,"about_ca_topic_score_gemma":0.9429024,"domain_scores_codex":[0.998494,0.0001014432,0.0001405192,0.0003589379,0.000526297,0.0003786606],"domain_scores_gemma":[0.993953,0.000389482,0.0003137902,0.0003843395,0.004483747,0.0004755887],"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":[0.00003041975,0.00001296768,0.0008214012,0.0001822927,0.00002570738,0.000006980814,0.000007109509,0.0002759235,0.00001515375,0.000161411,0.997555,0.0009057664],"study_design_scores_gemma":[0.0005212906,0.00002358102,0.03863925,0.0005769234,0.0001140711,0.00004510159,0.0003002688,0.001940115,0.0004250773,0.00113178,0.9561861,0.00009645717],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000848501,0.0000296517,0.0000138816,0.00003228225,0.00001480525,0.000005464837,0.9994088,0.00006963967,0.000340522],"genre_scores_gemma":[0.0003382245,0.00004078343,0.0001033617,0.00001916738,0.000004610308,0.00002422034,0.9984689,0.00002283421,0.0009778657],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09683657,"threshold_uncertainty_score":0.1948137,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02330457816832731,"score_gpt":0.2625825121031426,"score_spread":0.2392779339348153,"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."}}