{"id":"W2891129098","doi":"10.1002/cjce.23305","title":"Experimental methods in chemical engineering: Preface","year":2018,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Innovative Microfluidic and Catalytic Techniques Innovation","field":"Engineering","cited_by":46,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Computer science; Scale (ratio); Instrumentation (computer programming); Nanotechnology; Biochemical engineering; Process engineering; Management science; Mechanical engineering; Engineering; Materials science; Physics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.0004959141,0.0001833444,0.0002252783,0.0002621382,0.00002279908,0.00003483032,0.0003701538,0.0001320381,0.00005410253],"category_scores_gemma":[0.0001571947,0.0001599902,0.00006036456,0.0005631067,0.00009734667,0.00012033,0.00002088314,0.0005608959,0.000004754399],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000573035,"about_ca_system_score_gemma":0.0001176883,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007173132,"about_ca_topic_score_gemma":0.000001209582,"domain_scores_codex":[0.9989486,0.00000853023,0.0004595166,0.0000925194,0.0001266415,0.0003642305],"domain_scores_gemma":[0.9994555,0.00005063892,0.00004841485,0.0001680997,0.0001158375,0.0001615724],"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":[0.000003558684,0.000003955706,0.00001044078,0.00001443271,0.00002253516,0.00001008247,0.0003467859,0.0007472502,0.9957171,0.001468216,0.0008019891,0.0008536261],"study_design_scores_gemma":[0.0001850401,0.00002122133,0.00002278585,0.00007201445,0.000005991434,0.0001266347,0.00001288101,0.0152275,0.9786369,0.0000581999,0.00546139,0.0001695045],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7814907,0.001257456,0.2151457,0.0001823986,0.0008092411,0.000154691,0.000004827177,0.0001255498,0.0008294045],"genre_scores_gemma":[0.978038,4.392823e-7,0.0215028,0.00004816203,0.0003511825,0.000006123486,0.000002289881,0.00004314458,0.000007889408],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1965472,"threshold_uncertainty_score":0.6524212,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01464632519251352,"score_gpt":0.2668422655236219,"score_spread":0.2521959403311084,"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."}}