{"id":"W4404567106","doi":"10.3390/microplastics3040042","title":"Aerial Remote Sensing of Aquatic Microplastic Pollution: The State of the Science and How to Move It Forward","year":2024,"lang":"en","type":"article","venue":"Microplastics","topic":"Microplastics and Plastic Pollution","field":"Environmental Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fisheries and Oceans Canada; National Research Council Canada","funders":"","keywords":"Environmental science; Remote sensing; Hyperspectral imaging; Aquatic ecosystem; Drone; Pollution; Environmental monitoring; Microplastics; Citizen science; Aquatic environment; Computer science; Environmental resource management; Ecology; Geography; Environmental engineering; Biology","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":[0.004979535,0.001087447,0.001627378,0.002971706,0.0004692385,0.00379917,0.001586368,0.002354212,0.002351588],"category_scores_gemma":[0.008265041,0.000525208,0.001505241,0.003446057,0.001768671,0.005702824,0.001247764,0.001779774,0.0008606382],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00119645,"about_ca_system_score_gemma":0.002464887,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007169367,"about_ca_topic_score_gemma":0.007163084,"domain_scores_codex":[0.9980819,0.0005990081,0.0002147661,0.000488853,0.0005328112,0.00008268771],"domain_scores_gemma":[0.9883497,0.007426511,0.0007611709,0.0004560747,0.002839404,0.0001672941],"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":[0.0001172357,0.00005732125,0.006355313,0.02881745,0.0004942115,0.0001754109,0.000432248,0.001843842,0.007541858,0.010786,0.009966224,0.9334128],"study_design_scores_gemma":[0.00006591987,0.0006155972,0.04111757,0.05733792,0.002429757,0.001446385,0.00413828,0.01131889,0.01151453,0.05542667,0.8139088,0.0006797709],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.003340327,0.977017,0.01195191,0.004602647,0.0006120546,0.00005894253,0.0002840848,0.00007249453,0.002060681],"genre_scores_gemma":[0.03009483,0.93901,0.02625313,0.002271394,0.0009244469,0.0001033321,0.0005863385,0.00003889047,0.0007176803],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.007169367,"threshold_uncertainty_score":0.02633464,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008141616206478231,"score_gpt":0.2061293615350497,"score_spread":0.1979877453285715,"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."}}