{"id":"W2801781879","doi":"","title":"Using SEVIRI cloud time-series to assess the orbits number of LEO optical satellites for land mapping without cloud contamination","year":2017,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Economic and Technological Innovation","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Impact","funders":"","keywords":"Cloud computing; Series (stratigraphy); Meteorology; Computer science; Remote sensing; Environmental science; Time series; Geology; Geography; Operating system","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":[],"consensus_categories":[],"category_scores_codex":[0.00502971,0.0002280779,0.0005526721,0.0001460225,0.0003545701,0.0003675116,0.0009718276,0.0003370764,0.0000916827],"category_scores_gemma":[0.002347351,0.0002245145,0.0001550284,0.0001625207,0.0002453441,0.0001798174,0.0007099487,0.0003390835,0.00007257409],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001262957,"about_ca_system_score_gemma":0.00006626829,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002692584,"about_ca_topic_score_gemma":0.0001179591,"domain_scores_codex":[0.9980375,0.0002613992,0.0008226888,0.0005625307,0.00006373078,0.0002521439],"domain_scores_gemma":[0.9958951,0.0006824043,0.001216921,0.001309797,0.0008376997,0.0000580479],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00001417437,0.0001157089,0.05328665,0.0001253266,0.00008462539,3.054552e-7,0.0008966509,0.00007875961,0.0004854865,0.9397693,0.0001781286,0.004964882],"study_design_scores_gemma":[0.002004912,0.000005006439,0.07066847,0.003187842,0.0001155564,0.00002541286,0.0003788716,0.09930366,0.07768919,0.6276717,0.11697,0.001979398],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6060967,0.0003454679,0.3511532,0.006121404,0.0003747486,0.0007682445,0.0002056335,0.00008079218,0.03485383],"genre_scores_gemma":[0.9002352,0.0001523751,0.09466669,0.00007458223,0.00007054763,0.00008272367,0.0002227972,0.00003417996,0.004460861],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3120976,"threshold_uncertainty_score":0.9155436,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08718632907800136,"score_gpt":0.2818720230489768,"score_spread":0.1946856939709755,"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."}}