{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006830491,0.002770742,0.001439178,0.002061857,0.0006872621,0.001246523,0.003200586,0.002197208,0.006853855],"category_scores_gemma":[0.001437145,0.0005143988,0.001943882,0.00282335,0.0004203896,0.0009630595,0.001375586,0.00150502,0.01722139],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001377922,"about_ca_system_score_gemma":0.001413678,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04962057,"about_ca_topic_score_gemma":0.0948092,"domain_scores_codex":[0.9993845,0.00006226273,0.00006969777,0.0001970286,0.0001764485,0.0001100032],"domain_scores_gemma":[0.9994652,0.0000607477,0.00005974968,0.0001451077,0.0002095765,0.00005971425],"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":[0.0002962345,0.0001967154,0.01191358,0.00112808,0.0002553278,0.0001557841,0.00005491265,0.004983533,0.001455916,0.0004611209,0.9662892,0.01280955],"study_design_scores_gemma":[0.001322274,0.0001794012,0.08847929,0.0008741187,0.0002794331,0.000626253,0.0005853249,0.03632538,0.007095733,0.003453634,0.8604877,0.0002915559],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.002619606,0.0001710009,0.0002609983,0.00008045568,0.00006369559,0.00003051371,0.9951642,0.0009826848,0.0006269203],"genre_scores_gemma":[0.00302602,0.00004854208,0.0007712266,0.0000283871,0.000009357539,0.00004943538,0.9957275,0.00004029545,0.000299263],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.04962057,"threshold_uncertainty_score":0.09866351,"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."}}