{"id":"W4316096560","doi":"10.5194/isprs-annals-x-4-w1-2022-25-2023","title":"CONVOLUTIONAL SVM NETWORKS FOR DETECTION OF <i>GANODERMA BONINENSE</i> AT EARLY STAGE IN OIL PALM USING UAV AND MULTISPECTRAL PLEIADES IMAGES","year":2023,"lang":"en","type":"article","venue":"ISPRS annals of the photogrammetry, remote sensing and spatial information sciences","topic":"Date Palm Research Studies","field":"Agricultural and Biological Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"United Malacca Berhad","keywords":"Pleiades; Ganoderma; Multispectral image; Stage (stratigraphy); Support vector machine; Palm oil; Elaeis guineensis; Palm; Artificial intelligence; Computer science; Remote sensing; Biology; Geography; Computer vision; Agroforestry","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":[0.0009992332,0.0001108116,0.0001943741,0.00008927388,0.0004927973,0.0001025685,0.0001239488,0.00005700255,0.000001854662],"category_scores_gemma":[0.0003468219,0.00004942486,0.00007082293,0.000816657,0.0005879955,0.0002248604,0.0001680614,0.00007898713,3.505542e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001184903,"about_ca_system_score_gemma":0.00001256175,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.118386,"about_ca_topic_score_gemma":0.0328776,"domain_scores_codex":[0.9987575,0.00007747549,0.0003539353,0.0001508828,0.0003398178,0.0003203189],"domain_scores_gemma":[0.9991012,0.0003589075,0.0002535033,0.00004592374,0.0001880388,0.00005240501],"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":[0.00008140202,0.000007285411,0.006106128,0.0000424749,0.00001218925,2.779617e-7,0.000307834,0.001321372,0.1219469,0.000002005068,0.00004868389,0.8701234],"study_design_scores_gemma":[0.0001538348,0.0001508136,0.1412809,0.00006903263,0.000004533148,0.000004456,0.0006928198,0.8012173,0.05585092,0.0001193959,0.0003554562,0.0001004852],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9958532,0.000122779,0.00286935,0.0007045473,0.0001034544,0.000180028,0.0001004374,0.00001900681,0.0000472113],"genre_scores_gemma":[0.9992157,0.000459265,0.0001805868,0.00006895651,0.00003235898,4.656714e-7,0.00001093877,7.915575e-7,0.00003088667],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.870023,"threshold_uncertainty_score":0.9847699,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07182239318010372,"score_gpt":0.3127444512696963,"score_spread":0.2409220580895926,"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."}}