{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01850155,0.0009081474,0.001113505,0.001803075,0.0009165565,0.001675778,0.002124669,0.001372313,0.001398175],"category_scores_gemma":[0.08424882,0.0005471932,0.001221501,0.001572308,0.001530604,0.001558254,0.002497095,0.00189311,0.0003869846],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001012183,"about_ca_system_score_gemma":0.002563525,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002993305,"about_ca_topic_score_gemma":0.002039135,"domain_scores_codex":[0.9881254,0.006714419,0.0008259935,0.00114794,0.002872289,0.0003139369],"domain_scores_gemma":[0.925064,0.0567673,0.003020818,0.006058645,0.00873299,0.000356256],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004217448,0.0003732652,0.01166736,0.0002618778,0.0002027463,0.0002022924,0.0001614644,0.7093959,0.007217501,0.04600154,0.001518244,0.2225759],"study_design_scores_gemma":[0.00001221701,0.00007094812,0.0005191374,0.00001180976,0.000005410614,0.00002979112,0.00001123807,0.9913456,0.002308446,0.005264329,0.0004113055,0.000009855721],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01068319,0.00009498827,0.98813,0.00009448999,0.00003340962,0.00007687171,0.00004297006,0.0004858968,0.0003581603],"genre_scores_gemma":[0.3853286,0.000161063,0.6122919,0.0001854292,0.00006157396,0.0004739129,0.0005137931,0.000189985,0.000793677],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01850155,"threshold_uncertainty_score":0.09784675,"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."}}