{"id":"W2013071595","doi":"10.4028/www.scientific.net/amr.573-574.239","title":"Study on Casual Networks with Value Stream Mapping to Waste Disposal","year":2012,"lang":"en","type":"article","venue":"Advanced materials research","topic":"Cognitive Science and Mapping","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Value stream mapping; Casual; Lean manufacturing; Production (economics); Service (business); Process (computing); Computer science; Order (exchange); Value (mathematics); Operations research; Engineering; Industrial engineering; Risk analysis (engineering); Operations management; Business; Machine learning","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002043969,0.000590485,0.0005020684,0.001903502,0.0009626747,0.002494822,0.001172755,0.001065349,0.005333594],"category_scores_gemma":[0.01431247,0.0003825676,0.0008259404,0.002741914,0.001767515,0.004804374,0.001741482,0.001010181,0.0002715932],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001893485,"about_ca_system_score_gemma":0.0007199932,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004737648,"about_ca_topic_score_gemma":0.002914282,"domain_scores_codex":[0.9985452,0.0009081266,0.000037551,0.000191699,0.0002282427,0.00008929397],"domain_scores_gemma":[0.9926312,0.00554513,0.0006866092,0.0003214138,0.0005864446,0.0002293197],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001202318,0.0001311868,0.006816848,0.0002597093,0.00007285635,0.0007039605,0.001723595,0.2848078,0.001234756,0.6454685,0.001174681,0.05748584],"study_design_scores_gemma":[0.0000104647,0.00004419046,0.001433424,0.00005076038,0.00003031226,0.000212605,0.0007475691,0.6151574,0.0006016836,0.3777521,0.003940092,0.0000194198],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1236843,0.0006160938,0.8477705,0.001132582,0.00006165308,0.0001513463,0.0001178473,0.00007673282,0.02638894],"genre_scores_gemma":[0.8821751,0.001216254,0.1096427,0.0001153626,0.00008701297,0.000153727,0.0001209704,0.00004013878,0.006448753],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005333594,"threshold_uncertainty_score":0.01784265,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09784119282578262,"score_gpt":0.389747398898669,"score_spread":0.2919062060728864,"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."}}