{"id":"W2038806915","doi":"10.1117/12.421120","title":"&lt;title&gt;Combination of fuzzy sets and Dempster-Shafer theories in forest map updating using multispectral data&lt;/title&gt;","year":2001,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Remote-Sensing Image Classification","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Dempster–Shafer theory; Computer science; Multispectral image; Fuzzy set; Context (archaeology); Class (philosophy); Confusion; Fuzzy logic; Object (grammar); Artificial intelligence; Sensor fusion; Set (abstract data type); Data mining; Data set; Geography","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":[0.001172907,0.0003195763,0.0004892824,0.00132217,0.0002910877,0.001136156,0.000493469,0.0006629015,0.00372725],"category_scores_gemma":[0.001855663,0.0001483641,0.0004320271,0.001457173,0.000635946,0.001835353,0.0003516161,0.0006545603,0.001459887],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006217705,"about_ca_system_score_gemma":0.0002344754,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002077894,"about_ca_topic_score_gemma":0.002445895,"domain_scores_codex":[0.9995909,0.0000947376,0.00002460377,0.00006897035,0.0002025808,0.0000182494],"domain_scores_gemma":[0.9994006,0.0002773921,0.00003643217,0.00005157913,0.0002161096,0.00001789529],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002386835,0.00007326969,0.001947541,0.0004189686,0.0000785962,0.0004862655,0.0002026467,0.0460658,0.01176511,0.06431095,0.02750693,0.8469053],"study_design_scores_gemma":[0.0000345931,0.0001460316,0.004756922,0.0002038837,0.0001013679,0.0005229746,0.0001820879,0.7948479,0.02791137,0.08481668,0.08633415,0.0001419984],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02068359,0.009391627,0.9496518,0.002245777,0.002270082,0.0001294697,0.0001889046,0.0007093727,0.01472926],"genre_scores_gemma":[0.3073272,0.01163005,0.6407723,0.000701259,0.002596298,0.0001564839,0.0005058876,0.0002850316,0.03602545],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00372725,"threshold_uncertainty_score":0.01246893,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01833625143347684,"score_gpt":0.2467793789996066,"score_spread":0.2284431275661297,"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."}}