{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002631407,0.0001887637,0.000239076,0.0003315768,0.0004248155,0.0003775458,0.0009191268,0.00003862509,0.00001895848],"category_scores_gemma":[0.0001785396,0.000144142,0.00002067581,0.001233522,0.00008205803,0.00105699,0.0008490188,0.0002130086,0.0001911505],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001118314,"about_ca_system_score_gemma":0.00008069321,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005595047,"about_ca_topic_score_gemma":0.00001599965,"domain_scores_codex":[0.9964517,0.0004357603,0.0002352937,0.0006064115,0.00099986,0.001270996],"domain_scores_gemma":[0.9984013,0.0002910647,0.00004939334,0.0006543581,0.0002529975,0.0003509045],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0008592528,0.002660078,0.007786312,0.00007649746,0.0001258882,0.0004169258,0.02600435,0.01097755,0.7230426,0.04560461,0.0008405048,0.1816054],"study_design_scores_gemma":[0.006318901,0.01511393,0.1334316,0.001407704,0.00002749209,0.0001395389,0.04284952,0.003092434,0.7835516,0.002242479,0.00868307,0.003141646],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8929456,0.00002201102,0.1038389,0.0002462396,0.0005663754,0.001000858,0.000004341651,0.00009457859,0.001281132],"genre_scores_gemma":[0.9937097,0.000005902244,0.00533443,0.0001641872,0.0003545656,0.0001968314,0.000002281959,0.0000178044,0.0002143127],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1784638,"threshold_uncertainty_score":0.5877942,"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."}}