{"id":"W3047532104","doi":"10.5194/isprs-annals-v-3-2020-241-2020","title":"TREE SPECIES CLASSIFICATION BASED ON NEUTROSOPHIC LOGIC AND DEMPSTER-SHAFER THEORY","year":2020,"lang":"en","type":"article","venue":"ISPRS annals of the photogrammetry, remote sensing and spatial information sciences","topic":"Remote-Sensing Image Classification","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"CAS Key Laboratory of Digital Earth Science; Chinese Academy of Sciences; Ministry of Agriculture, Food and Rural Affairs; York University; Natural Sciences and Engineering Research Council of Canada; Ontario Ministry of Agriculture, Food and Rural Affairs","keywords":"Artificial intelligence; Multispectral image; Pattern recognition (psychology); Panchromatic film; Support vector machine; Computer science; Decision tree; Feature (linguistics); Dempster–Shafer theory; Remote sensing; Mathematics; Geography","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006442999,0.0001782857,0.0002073114,0.0001827965,0.0002439716,0.0002502495,0.0001725261,0.00008434668,0.000003872557],"category_scores_gemma":[0.000465637,0.0001297888,0.00007055315,0.0005693137,0.0004816494,0.000259615,0.00003842404,0.0001649405,0.000005574781],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001078524,"about_ca_system_score_gemma":0.00002647046,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007531803,"about_ca_topic_score_gemma":0.0001827853,"domain_scores_codex":[0.998704,0.0001123854,0.0004084058,0.0001777716,0.0003819985,0.0002154576],"domain_scores_gemma":[0.9991296,0.0001915317,0.0002080519,0.0002290551,0.0001408343,0.0001009255],"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":[0.00003795404,0.000004732368,0.00008260215,0.00006396999,0.000009226937,2.324042e-7,0.000515177,0.00601123,0.01110366,0.00007082962,0.0002551996,0.9818452],"study_design_scores_gemma":[0.0001500761,0.00009893921,0.009402079,0.00006626691,0.0000113298,0.000003928792,0.0003288834,0.968013,0.01983264,0.0006256221,0.001324867,0.0001423889],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1160018,0.00008341257,0.8642442,0.01127897,0.0003521979,0.0003754176,0.00001473689,0.0001746159,0.007474678],"genre_scores_gemma":[0.9962615,0.00007727353,0.00150649,0.002076233,0.0000543013,1.164553e-7,0.000005741394,0.000009282729,0.000009095994],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9817028,"threshold_uncertainty_score":0.5292632,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09428315560035072,"score_gpt":0.2815126445081678,"score_spread":0.187229488907817,"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."}}