{"id":"W2917842608","doi":"","title":"Odour AssessmentDecisionTree forOdourSampling andMeasurement","year":2016,"lang":"en","type":"article","venue":"Journal of Engineering Research and Technology","topic":"Odor and Emission Control Technologies","field":"Chemical Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Olfactometer; Sample (material); Sampling (signal processing); Point (geometry); Computer science; Test (biology); Engineering; Data mining; Artificial intelligence; Mathematics; Computer vision","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001102591,0.0001262342,0.0002838803,0.001057304,0.00006325895,0.0000275395,0.0003931245,0.0002159624,0.00003340604],"category_scores_gemma":[0.003676803,0.00007594878,0.00005058497,0.0004872337,0.00009819384,0.0001460754,0.0001806595,0.0006051739,0.00000573368],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001187298,"about_ca_system_score_gemma":0.00004349773,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000127912,"about_ca_topic_score_gemma":5.692671e-7,"domain_scores_codex":[0.9985119,0.00001020421,0.0003734105,0.0001591028,0.0004744527,0.0004708953],"domain_scores_gemma":[0.9985328,0.0004845101,0.00007939128,0.0002396973,0.0005211621,0.0001424443],"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":[0.00004591229,0.00004658973,0.001914034,0.00002411991,0.00007273753,0.00006110065,0.000006942647,0.00009967064,0.879346,0.009422288,0.001015679,0.1079449],"study_design_scores_gemma":[0.008368731,0.00298207,0.002439841,0.002484753,0.0000537017,0.001016872,0.0005459049,0.008109706,0.8156943,0.05648479,0.1009824,0.0008369637],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7059729,0.005114476,0.2712711,0.01614721,0.000426868,0.0002001155,0.000005321375,0.000477283,0.000384698],"genre_scores_gemma":[0.9935852,0.0004640428,0.005614053,0.000003334579,0.0001143572,0.000006155103,9.110889e-8,0.00002008549,0.0001926337],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2876123,"threshold_uncertainty_score":0.4401743,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09976632023850047,"score_gpt":0.3487797908034873,"score_spread":0.2490134705649868,"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."}}