{"id":"W4238794716","doi":"10.1007/978-3-319-21599-0_8","title":"Process Selection","year":2015,"lang":"en","type":"book-chapter","venue":"","topic":"Extraction and Separation Processes","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Process Research Ortech (Canada)","funders":"","keywords":"Selection (genetic algorithm); Process (computing); Computer science; Process management; Business; Artificial intelligence; Programming language","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":[0.001260343,0.002150272,0.001082957,0.002666696,0.001268137,0.00332903,0.00175412,0.001047067,0.05609825],"category_scores_gemma":[0.002379383,0.0006037307,0.001456018,0.002446729,0.0006784849,0.003492072,0.002220375,0.001515156,0.03661544],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008195642,"about_ca_system_score_gemma":0.00157623,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009920171,"about_ca_topic_score_gemma":0.001263562,"domain_scores_codex":[0.998637,0.0001460081,0.00007037957,0.0003846264,0.0006569166,0.0001050749],"domain_scores_gemma":[0.9992061,0.0002319619,0.00003183582,0.0002087704,0.0002859792,0.00003531999],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002339999,0.0001127681,0.0004562093,0.0005467489,0.00003870239,0.0002570461,0.0001371036,0.003506255,0.02121229,0.06489457,0.03638914,0.8722152],"study_design_scores_gemma":[0.00004692778,0.0002039952,0.001014364,0.0003571277,0.0001404014,0.001241563,0.0002354531,0.03716364,0.1211698,0.1117449,0.7265949,0.00008691259],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.005306529,0.002091526,0.8003018,0.0005931075,0.0004452084,0.0006448291,0.001363472,0.005652212,0.1836014],"genre_scores_gemma":[0.07852598,0.005884781,0.5457945,0.0009037395,0.000444238,0.0006857888,0.008515263,0.003311596,0.3559341],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.05609825,"threshold_uncertainty_score":0.1876674,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03564914166299721,"score_gpt":0.2726295416457755,"score_spread":0.2369803999827783,"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."}}