{"id":"W1986930867","doi":"10.3166/ts.27.79-108","title":"SAlgorithmes bayésiens pour le démélange supervisé, semi-supervisé et non-supervisé d’images hyperspectrales","year":2010,"lang":"fr","type":"article","venue":"Traitement du signal","topic":"Remote-Sensing Image Classification","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Humanities; Physics; Philosophy","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001017317,0.001026668,0.0008137709,0.0003940675,0.0003594685,0.000605364,0.0007953697,0.0005911969,0.002580627],"category_scores_gemma":[0.0001315868,0.001163546,0.0004602969,0.0005480179,0.0004320007,0.001223733,0.0001541017,0.001539322,0.001474061],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003162478,"about_ca_system_score_gemma":0.0003782627,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001081005,"about_ca_topic_score_gemma":0.0003864874,"domain_scores_codex":[0.9952797,0.0002578057,0.001046951,0.001105547,0.0008300069,0.001479959],"domain_scores_gemma":[0.9975078,0.0004338123,0.0001492041,0.001025489,0.0003368593,0.0005467991],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003383283,0.0007232665,0.001026605,0.0005153388,0.0003248565,0.0002065001,0.004715028,0.003265365,0.9082869,0.003700424,0.03042928,0.0467726],"study_design_scores_gemma":[0.005302802,0.0004999388,0.07592303,0.0008081619,0.000643782,0.000707617,0.005086145,0.5721935,0.2417154,0.00175787,0.09178329,0.003578425],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8231074,0.004906087,0.1099878,0.03493467,0.00445082,0.001502444,0.0005635908,0.00120827,0.01933893],"genre_scores_gemma":[0.9015889,0.00079586,0.09046658,0.0005078718,0.00245755,0.00004353443,0.0002791966,0.0003411862,0.003519354],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6665714,"threshold_uncertainty_score":0.9993034,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01514326712976246,"score_gpt":0.2317803692443514,"score_spread":0.216637102114589,"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."}}