{"id":"W2049562146","doi":"10.1002/masy.201200062","title":"Novel Test System for Gas Sensing Materials and Sensors","year":2013,"lang":"en","type":"article","venue":"Macromolecular Symposia","topic":"Analytical Chemistry and Sensors","field":"Chemical Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Analyte; Gas chromatography; Process engineering; Computer science; Test method; Chromatography; Environmental science; Materials science; Chemistry; Engineering; Mathematics; Statistics","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":[0.00008531385,0.0002179112,0.0002867237,0.00002675512,0.00008346108,0.0001055235,0.00008907772,0.0001460753,0.00004500189],"category_scores_gemma":[0.0001615005,0.0002072634,0.00007806966,0.00007265586,0.00005198817,0.00005419896,0.00005151206,0.00008795898,0.00005743784],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004829586,"about_ca_system_score_gemma":0.000007054366,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005687887,"about_ca_topic_score_gemma":2.772277e-7,"domain_scores_codex":[0.998892,0.00001048054,0.0002821822,0.0003217898,0.000128409,0.0003651374],"domain_scores_gemma":[0.9993116,0.0001515641,0.00005368733,0.0002339147,0.00007727185,0.0001719924],"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":[0.000006197689,0.00001499211,0.00001082302,0.0003009452,0.0000374648,0.00002098197,0.00003455429,0.00007548178,0.9979318,0.001423112,0.00005450452,0.00008914148],"study_design_scores_gemma":[0.0004126852,0.00002037176,0.00001898503,0.00009850339,0.00005605784,0.0002291188,0.00008032988,0.04459544,0.9537761,0.00003466354,0.0004192011,0.0002585846],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9704034,0.00006005839,0.02683788,0.0002592411,0.0000770019,0.0003269641,0.00004521386,0.0002024913,0.001787691],"genre_scores_gemma":[0.9948455,0.000002660799,0.004348842,0.00006684156,0.0001292354,0.00001421714,0.00002518886,0.00005043249,0.0005170884],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04451996,"threshold_uncertainty_score":0.8451955,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006626574026375273,"score_gpt":0.1994565960784127,"score_spread":0.1928300220520375,"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."}}