{"id":"W4295786002","doi":"10.21203/rs.3.rs-2052258/v1","title":"Hyperlocal US PM2.5 Trace Elements Super-learned","year":2022,"lang":"en","type":"preprint","venue":"Research Square","topic":"Air Quality and Health Impacts","field":"Environmental Science","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto; Concordia University","funders":"Novo Nordisk Fonden; Harvard Data Science Initiative, Harvard University; Novo Nordisk; National Institutes of Health; U.S. Environmental Protection Agency","keywords":"Particulates; TRACE (psycholinguistics); Environmental science; Meteorology; Geography; Chemistry","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":[0.0004288692,0.0006248099,0.000524126,0.0006813746,0.0002802246,0.0009284216,0.0007725161,0.0009787515,0.01067839],"category_scores_gemma":[0.002433456,0.0002637963,0.0004550122,0.0009545248,0.0004509111,0.002308641,0.00120923,0.001025248,0.002584627],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006714471,"about_ca_system_score_gemma":0.00071371,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009358498,"about_ca_topic_score_gemma":0.01406141,"domain_scores_codex":[0.9997815,0.00003682233,0.000006533846,0.00008074129,0.00005741207,0.00003693442],"domain_scores_gemma":[0.9995086,0.000173784,0.00003126671,0.000130098,0.0001179563,0.00003832156],"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":[0.00128829,0.0003233086,0.01362673,0.000533297,0.000248897,0.0003097934,0.0002678192,0.2517055,0.02568087,0.0263029,0.1083581,0.5713544],"study_design_scores_gemma":[0.00006857658,0.0001095071,0.005825595,0.0000376823,0.00006776833,0.0001152249,0.0001595247,0.9188806,0.0111396,0.04257486,0.02098478,0.00003641356],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2557066,0.003704166,0.6565093,0.007557841,0.001831063,0.0001337829,0.0104709,0.01742477,0.04666154],"genre_scores_gemma":[0.8990175,0.001340478,0.06119411,0.001336169,0.0006801646,0.00007703347,0.006568046,0.001012173,0.02877425],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01067839,"threshold_uncertainty_score":0.03572273,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1975776321437115,"score_gpt":0.4706649109391478,"score_spread":0.2730872787954363,"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."}}