{"id":"W4236330837","doi":"10.5194/acp-2016-296","title":"Temporal and spectral cloud screening of polar-winter aerosol optical depth (AOD): impact of homogeneous and inhomogeneous clouds and crystal layers on climatological-scale AODs","year":2016,"lang":"en","type":"preprint","venue":"","topic":"Atmospheric aerosols and clouds","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University; Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Aerosol; Environmental science; Lidar; Atmospheric sciences; Homogeneous; Polar; Mode (computer interface); Remote sensing; Meteorology; Geology; Geography; Physics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004286371,0.0004030879,0.0002502042,0.0002100471,0.0001992557,0.0005812617,0.0003271726,0.0003719518,0.0005651378],"category_scores_gemma":[0.0007979985,0.0002367307,0.0005041523,0.0002880819,0.0002292464,0.000393016,0.0002151132,0.0002258961,0.00009884884],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008940166,"about_ca_system_score_gemma":0.000790642,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1179002,"about_ca_topic_score_gemma":0.07047241,"domain_scores_codex":[0.9998763,0.00002602642,0.00001092488,0.0000371023,0.00002277331,0.00002681019],"domain_scores_gemma":[0.9996594,0.0001603489,0.00004374232,0.00002865823,0.00007184259,0.0000360219],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008291086,0.0002711003,0.553093,0.0001444513,0.0004333642,0.000332933,0.00009649726,0.3959923,0.03721697,0.0004107786,0.0004819009,0.01069763],"study_design_scores_gemma":[0.0001067503,0.0001933529,0.3914198,0.0000218298,0.0001538854,0.00008322802,0.0001175368,0.5903722,0.01669832,0.0001235167,0.0006827282,0.00002686412],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9987087,0.00005222491,0.0003231319,0.00001990182,0.000006641774,0.00000704633,0.0004334679,0.00003153642,0.000417313],"genre_scores_gemma":[0.9992619,0.00002483735,0.0002818234,0.000006532698,0.000001534344,0.000002678137,0.0003166542,0.000009184378,0.00009477905],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1179002,"threshold_uncertainty_score":0.2344279,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01355493592530667,"score_gpt":0.2560481057156258,"score_spread":0.2424931697903191,"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."}}