{"id":"W2344673613","doi":"10.5220/0005628204070414","title":"Statistical Measurement Validation with Application to Electronic Nose Technology","year":2016,"lang":"en","type":"article","venue":"","topic":"Advanced Chemical Sensor Technologies","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Electronic nose; Odor; Computer science; Artificial intelligence; Sensor array; Pattern recognition (psychology); Sampling (signal processing); Key (lock); Range (aeronautics); Data mining; Machine learning; Computer vision; Engineering","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":[0.00002287374,0.00008475389,0.00007437568,0.00007127211,0.00001310197,0.000003829879,0.0001031309,0.00006678821,0.00002256749],"category_scores_gemma":[0.0000663808,0.00005255772,0.000005406253,0.0002046305,0.00003284416,0.00004154472,0.00001629827,0.00006330828,0.0001427333],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00031741,"about_ca_system_score_gemma":0.000003320873,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":8.832604e-7,"about_ca_topic_score_gemma":0.00001132559,"domain_scores_codex":[0.9993784,0.000001823985,0.00009116788,0.0001489985,0.0001391175,0.0002404494],"domain_scores_gemma":[0.9996797,0.00001872218,0.000009147485,0.0002105381,0.00005182029,0.00003004864],"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":[0.000006129727,0.000006498174,0.0001144842,0.000003968144,0.000008393214,3.156976e-7,0.000001403311,0.0006648144,0.8898588,0.02899479,0.0001642206,0.08017619],"study_design_scores_gemma":[0.0001435811,0.00006213899,0.00008090312,0.00000841889,0.000004274461,0.000002522387,0.000009781515,0.0001824369,0.9800955,0.01177454,0.007525095,0.000110809],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1197576,0.00001608156,0.8769953,0.0008755762,0.000007163879,0.000167228,0.00000202668,0.001592982,0.0005861255],"genre_scores_gemma":[0.9833257,0.00001250765,0.01648204,0.00001360761,0.00000780248,0.0001140043,0.000001224987,0.000017039,0.00002608012],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8635681,"threshold_uncertainty_score":0.2143242,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005388402866849933,"score_gpt":0.2061384658652831,"score_spread":0.2007500629984332,"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."}}