{"id":"W3209917970","doi":"10.3390/app11136140","title":"Baseline Air Monitoring of Fine Particulate Matter and Trace Elements in Ontario’s Far North, Canada","year":2021,"lang":"en","type":"article","venue":"Applied Sciences","topic":"Air Quality and Health Impacts","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada; Ministry of the Environment, Conservation and Parks","funders":"Environment and Climate Change Canada","keywords":"Particulates; Environmental science; Baseline (sea); Air quality index; Air pollution; Trace gas; Pollutant; Air pollutants; Meteorology; Geography; Geology; Oceanography","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002364544,0.0003824381,0.0003260579,0.0009569314,0.003101831,0.0009524145,0.0006306701,0.0002689519,0.001297483],"category_scores_gemma":[0.0004292256,0.0002829225,0.0002413471,0.001881549,0.0004145318,0.0003324439,0.0005262413,0.0002770535,0.0003442723],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01943322,"about_ca_system_score_gemma":0.0295782,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.994441,"about_ca_topic_score_gemma":0.9986237,"domain_scores_codex":[0.9992834,0.00001814482,0.00002356439,0.0001227792,0.0004090847,0.0001430872],"domain_scores_gemma":[0.9987198,0.00002306936,0.00007281739,0.00001973389,0.001037915,0.000126574],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003834101,0.0002247351,0.8916156,0.000471477,0.0001347453,0.0009577859,0.006340947,0.00156216,0.03648802,0.0005256599,0.01436052,0.04693501],"study_design_scores_gemma":[0.00000945402,0.00005981088,0.9798855,0.00003774668,0.00002016204,0.00006373232,0.001905171,0.0007787003,0.001416455,0.00003223402,0.0157719,0.00001908572],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9673414,0.0008889212,0.001040062,0.0003162324,0.00003217733,0.0003042782,0.01032322,0.0001099473,0.01964373],"genre_scores_gemma":[0.9787858,0.0006690234,0.002355353,0.0001751574,0.000009907892,0.00009821929,0.004849256,0.00002433636,0.01303298],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01943322,"threshold_uncertainty_score":0.1409985,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03223907702099207,"score_gpt":0.2665030544534717,"score_spread":0.2342639774324796,"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."}}