{"id":"W4396580471","doi":"10.4095/g274826","title":"Fugitive dust monitoring and characterization techniques: challenges and opportunities","year":2022,"lang":"en","type":"report","venue":"","topic":"Air Quality Monitoring and Forecasting","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Characterization (materials science); Environmental science; Astrobiology; Remote sensing; Nanotechnology; Geography; Materials science; Physics","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":[0.005839767,0.001452778,0.001125836,0.002439807,0.001076486,0.00467685,0.003401292,0.002415595,0.004376045],"category_scores_gemma":[0.003140599,0.0004054487,0.0006817657,0.002019696,0.001387139,0.005761344,0.001538601,0.001363888,0.002823242],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001310152,"about_ca_system_score_gemma":0.001913809,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01114582,"about_ca_topic_score_gemma":0.02046597,"domain_scores_codex":[0.9976555,0.0003846658,0.00008297454,0.0003627732,0.00131148,0.0002025496],"domain_scores_gemma":[0.9960019,0.001311179,0.0002917206,0.0006263659,0.001559613,0.0002092446],"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":[0.0002174998,0.0005340592,0.01184422,0.0009950089,0.00009636476,0.0002152623,0.0004654311,0.003091692,0.09708932,0.01100045,0.05089277,0.8235579],"study_design_scores_gemma":[0.00006959723,0.0008250916,0.03866458,0.0007805913,0.0002169344,0.001602647,0.00202939,0.035398,0.3150814,0.04441828,0.5606869,0.0002265552],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.1022415,0.09960274,0.6616648,0.03014421,0.002344832,0.0009068766,0.009607579,0.01275018,0.08073732],"genre_scores_gemma":[0.2857265,0.04946892,0.5832406,0.003269543,0.001360033,0.0004846468,0.01414683,0.001381203,0.06092174],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.01114582,"threshold_uncertainty_score":0.03088403,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1686055489287555,"score_gpt":0.306960961178714,"score_spread":0.1383554122499586,"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."}}