{"id":"W3191488773","doi":"10.21203/rs.3.rs-806261/v1","title":"Application of Convolutional Neural Networks for Prediction of 1 Disinfection By-Products","year":2021,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Chemical Sensor Technologies","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Water Network","keywords":"Convolutional neural network; Dimensionality reduction; Artificial neural network; Curse of dimensionality; Computer science; Artificial intelligence; Haloacetic acids; Test set; Fluorescence spectroscopy; Superposition principle; Data set; Fluorescence; Pattern recognition (psychology); Biological system; Machine learning; Environmental science; Water treatment; Mathematics; Environmental engineering; Physics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001638308,0.000132413,0.0002475589,0.0001281453,0.00003809116,0.00001215003,0.0001934063,0.0003802998,0.000004796971],"category_scores_gemma":[0.0005013871,0.000145392,0.00008439763,0.0003598625,0.0001718652,0.00006267284,0.0002061764,0.0007025566,2.996122e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002292248,"about_ca_system_score_gemma":0.00001450498,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002198425,"about_ca_topic_score_gemma":0.000002619683,"domain_scores_codex":[0.9987037,0.00003288792,0.0003128127,0.0003178871,0.0003677355,0.0002649565],"domain_scores_gemma":[0.9984644,0.0002088467,0.00007874233,0.0004493821,0.000765744,0.00003289722],"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":[0.00002645723,0.00006064975,0.001096087,0.002694476,0.00005318311,1.85863e-7,0.00001924299,0.6007676,0.383935,0.0002514722,0.001458678,0.009636928],"study_design_scores_gemma":[0.0001544219,0.00005732707,0.001620403,0.0001506068,0.00001052892,9.126865e-7,0.00007039531,0.6354809,0.3607481,0.001191878,0.0004194467,0.00009506963],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4651644,0.003871436,0.5275108,0.0001295135,0.0003209607,0.00152669,0.0009319876,0.0004733486,0.00007082827],"genre_scores_gemma":[0.9962617,0.0004524307,0.001058602,5.092138e-7,0.0001438295,0.0003863549,0.00165129,0.00003267263,0.00001266496],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5310972,"threshold_uncertainty_score":0.5928913,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03315313403667891,"score_gpt":0.3221673129065207,"score_spread":0.2890141788698418,"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."}}