{"id":"W116459826","doi":"10.1007/978-94-007-1359-8_53","title":"Forecasting O3, PM25 and NO2 Hourly Spot Concentrations Using an Updatable MOS Methodology","year":2011,"lang":"en","type":"book-chapter","venue":"NATO science for peace and security series. C, Environmental security","topic":"Air Quality Monitoring and Forecasting","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"Environmental science; Air quality index; Meteorology; Variance (accounting); Ozone; Nitrogen dioxide; Particulates; Statistics; Data set; Set (abstract data type); Computer science; Mathematics; Geography; Chemistry; Economics","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","sts"],"consensus_categories":["sts"],"category_scores_codex":[0.002310739,0.0007201092,0.0007227378,0.0001338119,0.002026303,0.0002331547,0.0006403616,0.0005321074,0.0006855005],"category_scores_gemma":[0.000139127,0.0007673601,0.0001394153,0.0001305838,0.004402705,0.002264295,0.001031081,0.0007705443,0.00001981974],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005412982,"about_ca_system_score_gemma":0.00007849893,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006761681,"about_ca_topic_score_gemma":0.0003999456,"domain_scores_codex":[0.9956236,0.0001137604,0.0006896423,0.001716016,0.0008055458,0.001051394],"domain_scores_gemma":[0.9979611,0.0001823764,0.0005337914,0.0006220436,0.00002231376,0.0006783609],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.003633902,0.004474651,0.1042154,0.002947904,0.001074578,0.0005790335,0.3118177,0.001727881,0.09418784,0.2952354,0.004791563,0.1753142],"study_design_scores_gemma":[0.005329279,0.005583626,0.003929965,0.0008651869,0.00146601,0.002125012,0.01389294,0.0998597,0.02478137,0.381714,0.4497283,0.01072461],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.968433,0.001574259,0.001167247,0.0001280986,0.0007307411,0.001797686,0.001688608,0.0001463235,0.02433401],"genre_scores_gemma":[0.9817426,0.0008452238,0.01174781,0.0001727609,0.0003298821,0.00004096333,0.0002644433,0.0001126115,0.004743756],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4449367,"threshold_uncertainty_score":0.9994777,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1057186639447514,"score_gpt":0.2894327026484927,"score_spread":0.1837140387037413,"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."}}