{"id":"W4401067356","doi":"10.1145/3670105.3670169","title":"Optimizing Safety In IoT Water Plants: From Critical Importance To Innovative Solutions","year":2024,"lang":"en","type":"article","venue":"","topic":"Water Quality Monitoring Technologies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Internet of Things; Computer science; Computer security","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":[0.000953336,0.0007046803,0.0003214898,0.0004750062,0.0005528021,0.002061111,0.0007160358,0.001022988,0.001231429],"category_scores_gemma":[0.002066834,0.0001884494,0.0002755115,0.0004260779,0.00116733,0.002773619,0.001416163,0.0009147222,0.0002466709],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009403491,"about_ca_system_score_gemma":0.00125269,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001194487,"about_ca_topic_score_gemma":0.001905853,"domain_scores_codex":[0.9993188,0.0001920294,0.00002933168,0.00009085745,0.0002772411,0.00009180255],"domain_scores_gemma":[0.9989435,0.0003480295,0.0002135439,0.0001028603,0.0003177776,0.00007427113],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002350665,0.000307007,0.01200662,0.0008644444,0.0001307083,0.0003180447,0.0004223296,0.3711693,0.04323034,0.05687914,0.004240746,0.5101962],"study_design_scores_gemma":[0.00002890042,0.0005813374,0.004815848,0.0003026882,0.00008414179,0.0002424973,0.001885406,0.8178967,0.03094992,0.1147957,0.02835468,0.00006223148],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.2135394,0.009586362,0.7391678,0.01219677,0.0003309152,0.0001315394,0.0001020798,0.0005799202,0.02436516],"genre_scores_gemma":[0.9574733,0.003361287,0.0359908,0.0002637209,0.0001034807,0.00003196882,0.00005498258,0.00003871911,0.002681738],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.002061111,"threshold_uncertainty_score":0.006822765,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04319212488810044,"score_gpt":0.2985288270925667,"score_spread":0.2553367022044662,"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."}}