{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","research_integrity","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.006351212,0.0003227254,0.0004205605,0.0001878897,0.001096913,0.0001602761,0.001305651,0.0003814658,0.0840376],"category_scores_gemma":[0.0007136535,0.0003250785,0.0001779005,0.0005978958,0.0004719615,0.0001752338,0.005619372,0.004140906,0.003228223],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002183679,"about_ca_system_score_gemma":0.0004133647,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00649528,"about_ca_topic_score_gemma":0.0006859049,"domain_scores_codex":[0.9911084,0.001991978,0.0005889944,0.001104763,0.003538733,0.001667092],"domain_scores_gemma":[0.9974127,0.0003924246,0.0001171541,0.001204888,0.00004563442,0.0008272462],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0009437115,0.002811709,0.2914233,0.003972019,0.0001571897,0.0008790583,0.01243828,0.03060327,0.000468482,0.001816725,0.4885925,0.1658938],"study_design_scores_gemma":[0.0006527603,0.000761193,0.1554158,0.0001586136,0.00001229025,0.00001065986,0.002178578,0.002887741,0.000109785,0.004640892,0.8325995,0.000572114],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9178436,0.0006885551,0.000104079,0.01780075,0.0005083975,0.002663156,0.000359771,0.0001950541,0.05983666],"genre_scores_gemma":[0.9786413,0.0009901276,0.001717562,0.00159239,0.0003614085,0.0006865705,0.0003324717,0.0001091022,0.01556904],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.344007,"threshold_uncertainty_score":0.9999201,"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."}}