{"id":"W4388949800","doi":"10.1109/iotsms59855.2023.10325803","title":"AI-Enabled Plastic Pollution Monitoring System for Toronto Waterways","year":2023,"lang":"en","type":"article","venue":"","topic":"Microplastics and Plastic Pollution","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Microplastics; Plastic pollution; Pollution; Cloud computing; Computer science; Environmental monitoring; Environmental science; Aquatic ecosystem; Noise pollution; Environmental pollution; Environmental protection; Environmental engineering; Ecology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0001823602,0.0005506796,0.0003954828,0.0009713947,0.0007200996,0.0006000375,0.0008387567,0.0004050176,0.009655906],"category_scores_gemma":[0.0003686784,0.0001493578,0.0002007307,0.0007513676,0.0002168631,0.0004801128,0.0005883015,0.0003207808,0.002040466],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001821975,"about_ca_system_score_gemma":0.001428036,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08327974,"about_ca_topic_score_gemma":0.1270867,"domain_scores_codex":[0.999713,0.00001678206,0.0000151194,0.00008179176,0.0001282976,0.00004486967],"domain_scores_gemma":[0.9997005,0.00001942256,0.00002116385,0.00002566703,0.0001885702,0.00004460638],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0030015,0.000881658,0.08560669,0.001107567,0.0002467838,0.003125204,0.00198927,0.05877263,0.3187234,0.004503557,0.1531495,0.3688921],"study_design_scores_gemma":[0.0001874718,0.000453992,0.07156567,0.00009598326,0.0001288861,0.000363737,0.0008726754,0.7659354,0.0713365,0.00131706,0.08755159,0.000191117],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6281415,0.0006957087,0.167183,0.001708786,0.0006272899,0.001231857,0.0213623,0.09277228,0.08627742],"genre_scores_gemma":[0.9454356,0.000147264,0.02934662,0.0002923611,0.00004296424,0.0003047851,0.005482385,0.0002046732,0.01874332],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9167203,"threshold_uncertainty_score":0.16559,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01185402580812111,"score_gpt":0.2217800308769879,"score_spread":0.2099260050688667,"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."}}