{"id":"W4411570452","doi":"10.30564/jees.v7i6.9315","title":"Detecting Plastic Pollution in Aquatic Environment Using Remote Sensing Technology: Cost-Saving Method in Pollution and Risk Management for Developing Countries","year":2025,"lang":"en","type":"article","venue":"Journal of Environmental & Earth Sciences","topic":"Microplastics and Plastic Pollution","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"Central University of Technology","keywords":"Pollution; Environmental science; Environmental planning; Developing country; Environmental resource management; Risk analysis (engineering); Environmental protection; Business; Environmental engineering; Economic growth; Economics; Ecology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001796189,0.0001800233,0.0002536918,0.000584379,0.0003845546,0.00005656989,0.0001523934,0.00009144884,0.00001972996],"category_scores_gemma":[0.0001515314,0.0001685882,0.00004318585,0.0004576317,0.0004208323,0.0003012975,0.0001831276,0.0002154212,0.000004186301],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005617836,"about_ca_system_score_gemma":0.00003277023,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001441105,"about_ca_topic_score_gemma":0.0003073777,"domain_scores_codex":[0.9982033,0.0001133921,0.0006128987,0.0003360157,0.0003405314,0.0003939063],"domain_scores_gemma":[0.9991713,0.0002623854,0.000430966,0.00008522775,0.000001917972,0.00004820322],"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":[0.0002163079,0.00009528173,0.2066617,0.00007924662,0.00006574584,0.00005265691,0.0006219473,0.3357109,0.08268144,0.0004107132,0.000007586782,0.3733964],"study_design_scores_gemma":[0.001857428,0.0002758601,0.4107911,0.0008445774,0.0001412386,0.0001581125,0.001858334,0.5682744,0.007611071,0.006082862,0.001692244,0.0004128109],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6444259,0.0002130537,0.35476,0.0001477366,0.0001521761,0.0002459711,0.000006355033,0.000003694554,0.00004510459],"genre_scores_gemma":[0.7701879,0.0007082272,0.2290126,0.00006030993,0.00001236122,7.804394e-7,3.224559e-7,0.000005482259,0.0000120154],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3729836,"threshold_uncertainty_score":0.6874827,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01205187075544441,"score_gpt":0.255683057718973,"score_spread":0.2436311869635286,"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."}}