{"id":"W4393516608","doi":"10.5281/zenodo.10407272","title":"Absorbing Aerosol Optical Central Height (AOCH) retrieved from TROPOMI with UIowa's AOCH-O2AB algorithm","year":2023,"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":"Aerosol; Remote sensing; Environmental science; Atmospheric sciences; Meteorology; Algorithm; Geography; Mathematics; Geology","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.000686993,0.0004231794,0.0003983386,0.00008424896,0.002268965,0.0009487565,0.001722198,0.000285094,0.01286492],"category_scores_gemma":[0.0006576408,0.0004045363,0.0001020225,0.0007877317,0.0005204295,0.0002901379,0.002606432,0.001052393,0.04948855],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006611106,"about_ca_system_score_gemma":0.000006746995,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001033953,"about_ca_topic_score_gemma":0.000006908088,"domain_scores_codex":[0.9959205,0.0003834854,0.0004905376,0.00106102,0.0011739,0.0009704909],"domain_scores_gemma":[0.9981425,0.00009706966,0.0002620189,0.0009205625,0.00009858317,0.0004792819],"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":[0.00008081378,0.0001158562,0.000004938878,0.00003636259,0.00007207487,0.0001198062,0.0002541591,0.00009918258,0.0002318166,0.000007630879,0.9710274,0.02794992],"study_design_scores_gemma":[0.0006034818,0.0003289739,0.0008020391,0.0001422755,0.00006428814,0.00005427443,0.0002108143,0.0005544524,0.0002242106,0.00002739768,0.9964601,0.000527713],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00443963,0.00004366121,0.00309069,0.0004702875,0.0006709743,0.0007829397,0.9836637,0.001448443,0.005389633],"genre_scores_gemma":[0.001411412,0.0001600606,0.001765717,0.00008234592,0.0009039417,1.594156e-7,0.9927597,0.001841636,0.001074996],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03662362,"threshold_uncertainty_score":0.9998407,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03171280011379522,"score_gpt":0.2375503404460356,"score_spread":0.2058375403322404,"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."}}