{"id":"W2100072750","doi":"10.5430/air.v1n1p31","title":"Performance analysis of neuro swarm optimization algorithm applied on detecting proportion of components in manhole gas mixture","year":2012,"lang":"en","type":"article","venue":"Artificial Intelligence Research","topic":"Advanced Chemical Sensor Technologies","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Methane; Component (thermodynamics); Swarm behaviour; Hydrogen sulfide; Sensitivity (control systems); Carbon monoxide; Computer science; Algorithm; Process engineering; Materials science; Engineering; Chemistry; Artificial intelligence; Electronic engineering; Organic chemistry","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001790409,0.0007880717,0.0008254188,0.0006097223,0.0004856217,0.0008865281,0.0004344926,0.0009426128,0.0009676965],"category_scores_gemma":[0.004433816,0.0001837019,0.0003777591,0.0004904694,0.0004405853,0.0004139731,0.0003747706,0.0005530121,0.0001828393],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008060667,"about_ca_system_score_gemma":0.001077384,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01113345,"about_ca_topic_score_gemma":0.003829947,"domain_scores_codex":[0.9993172,0.0002686609,0.0000438835,0.00009170563,0.0001699785,0.0001086521],"domain_scores_gemma":[0.9973409,0.001717361,0.0001635744,0.00008057769,0.0006353655,0.00006226627],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003997692,0.00007290851,0.003537943,0.0001031766,0.00007249563,0.00005373066,0.00006014829,0.96231,0.002873466,0.001203674,0.0004718719,0.02884079],"study_design_scores_gemma":[0.000003830952,0.00005930991,0.0006503202,0.000004344288,0.000006442854,0.000009971277,0.00001450351,0.9978295,0.001246599,0.0001065175,0.00006514329,0.000003543382],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.6288657,0.00182597,0.3522078,0.0006758647,0.0001601961,0.0001128994,0.0001065759,0.0008538766,0.01519112],"genre_scores_gemma":[0.9709508,0.0002925188,0.02710823,0.00004601912,0.00001129959,0.00004548463,0.000095326,0.00004137365,0.001408959],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.01113345,"threshold_uncertainty_score":0.02213728,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1066371448699131,"score_gpt":0.3417188493709027,"score_spread":0.2350817045009896,"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."}}