{"id":"W2521581589","doi":"","title":"Evaluation de la sensibilité de l’instrument FCI à bord du nouveau satellite Meteosat Troisième Génération imageur (MTG-I) aux variations de la quantité d’aérosols d’origine désertique dans l’atmosphère","year":2016,"lang":"fr","type":"dissertation","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Remote-Sensing Image Classification","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Impact","funders":"","keywords":"Physics; Humanities; Meteorological satellite; Forestry; Geography; Art; Satellite; Geostationary orbit","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001423015,0.0006344344,0.0004587742,0.0005714437,0.0002833453,0.0007131134,0.0006409501,0.0009281341,0.000817463],"category_scores_gemma":[0.002557861,0.0002874621,0.0006529447,0.0004546508,0.0003325425,0.0005161702,0.0004790419,0.000380282,0.0002673719],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005776189,"about_ca_system_score_gemma":0.0004366623,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003562562,"about_ca_topic_score_gemma":0.00211792,"domain_scores_codex":[0.9993644,0.0001702867,0.0000226769,0.0001507467,0.0002220824,0.00006979901],"domain_scores_gemma":[0.9990884,0.0004550397,0.0001012695,0.0001303661,0.0001952059,0.00002968972],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001179886,0.0003807881,0.1123974,0.0004677826,0.0005016007,0.0001809943,0.0005879169,0.4256103,0.3009605,0.001414319,0.0006918919,0.1556265],"study_design_scores_gemma":[0.00007235011,0.001766036,0.07472944,0.00003972664,0.0001627806,0.000277203,0.0002104341,0.7182133,0.2010285,0.0003133949,0.003092652,0.00009418127],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9310942,0.0002124521,0.06504315,0.00008249177,0.00003617835,0.00009164664,0.0003190177,0.0007519301,0.002368919],"genre_scores_gemma":[0.9639141,0.0001207553,0.0349658,0.00003413376,0.000005546438,0.0000635488,0.0003728369,0.00004358819,0.0004797279],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003562562,"threshold_uncertainty_score":0.007525742,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01061872388378055,"score_gpt":0.2528988805421232,"score_spread":0.2422801566583426,"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."}}