{"id":"W2415938545","doi":"10.4242/balisagevol10.nordin01","title":"Markup and Canada's National Model Building Codes","year":2013,"lang":"en","type":"article","venue":"Balisage series on markup technologies","topic":"Optics and Image Analysis","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Markup language; Political science; World Wide Web; XML","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":[0.005539177,0.0006555223,0.0004042658,0.005346947,0.007562468,0.01019436,0.003050833,0.001844732,0.01587483],"category_scores_gemma":[0.0201352,0.0005765686,0.0008102387,0.008325744,0.00472408,0.003659353,0.002748496,0.002337675,0.002188102],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.1015387,"about_ca_system_score_gemma":0.1803699,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9814588,"about_ca_topic_score_gemma":0.9800745,"domain_scores_codex":[0.9856284,0.0008344214,0.0003991847,0.0005459545,0.01113811,0.001453938],"domain_scores_gemma":[0.979677,0.002271512,0.000619635,0.002065178,0.01429244,0.00107416],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002574237,0.00001730592,0.0008784133,0.0001114278,0.000007115575,0.0001169707,0.001253418,0.003126649,0.0003681164,0.8316052,0.09462471,0.06786484],"study_design_scores_gemma":[0.00001051838,0.00001268082,0.002227203,0.0002464289,0.00001128367,0.00009129859,0.0007450078,0.003131278,0.00086225,0.03038088,0.9622018,0.00007939151],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.01765019,0.004835141,0.05680211,0.03694902,0.00129971,0.0003105072,0.005286836,0.002723737,0.8741428],"genre_scores_gemma":[0.3487322,0.0111667,0.1593069,0.006500936,0.0003608352,0.0005576056,0.007873112,0.001849509,0.4636523],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8984613,"threshold_uncertainty_score":0.7367184,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008138877558754322,"score_gpt":0.1904909705946607,"score_spread":0.1823520930359064,"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."}}