{"id":"W4393452781","doi":"10.5281/zenodo.6189451","title":"Evaluation data for \"Global, high-resolution, reduced-complexity air quality modeling for PM2.5 using InMAP (Intervention Model for Air Pollution)\"","year":2021,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Air Quality Monitoring and Forecasting","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Air quality index; Environmental science; Air pollution; Meteorology; Pollution; Intervention (counseling); High resolution; Remote sensing; Geography; Chemistry","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002351851,0.001504897,0.0007780583,0.001298991,0.0005797471,0.001071993,0.002611839,0.000681388,0.09641279],"category_scores_gemma":[0.006072661,0.0004999061,0.001021498,0.001930451,0.0002328673,0.001599334,0.001086544,0.001215957,0.0397195],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001279968,"about_ca_system_score_gemma":0.001434045,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02680902,"about_ca_topic_score_gemma":0.02099662,"domain_scores_codex":[0.9988972,0.0001925134,0.00008426867,0.0001595344,0.0005551548,0.0001112536],"domain_scores_gemma":[0.9967784,0.0007587824,0.0001653343,0.0005906479,0.001511939,0.0001949436],"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":[0.000252638,0.0001290484,0.002695252,0.0004229555,0.00005539832,0.00004835085,0.00002746389,0.01226392,0.0007196163,0.000918809,0.9708219,0.0116446],"study_design_scores_gemma":[0.001577903,0.0003642401,0.03213387,0.0004412354,0.0001259866,0.0001733438,0.0002937702,0.1084275,0.01669146,0.005141696,0.8344537,0.0001752152],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.004031611,0.00004288115,0.003660258,0.0003245406,0.0001452708,0.0001734232,0.9727114,0.008094108,0.01081655],"genre_scores_gemma":[0.01070855,0.00006579756,0.005161005,0.0001565404,0.00003262187,0.0003783946,0.9777228,0.002166308,0.003608125],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09641279,"threshold_uncertainty_score":0.3225329,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3106374137450872,"score_gpt":0.383926445371752,"score_spread":0.07328903162666478,"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."}}