{"id":"W4313004348","doi":"10.34028/iajit/20/1/2","title":"On Satellite Imagery of Land Cover Classification for Agricultural Development","year":2022,"lang":"en","type":"article","venue":"The International Arab Journal of Information Technology","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Land cover; Computer science; Cluster analysis; Remote sensing; Satellite imagery; Fuzzy logic; Vegetation (pathology); Land use; Satellite; Fuzzy clustering; Segmentation; Cover (algebra); Geography; Artificial intelligence; Ecology","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":[0.0002243907,0.0004169804,0.0002166275,0.002084751,0.0003141027,0.0005486973,0.0002311934,0.0002970262,0.001328976],"category_scores_gemma":[0.000573988,0.000089623,0.0003332496,0.002463535,0.0001561605,0.0003336326,0.0002127256,0.0002160415,0.0007864839],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004128131,"about_ca_system_score_gemma":0.0004479992,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01679204,"about_ca_topic_score_gemma":0.02768937,"domain_scores_codex":[0.9997726,0.00003517875,0.00001408273,0.00004991742,0.0001060454,0.000022159],"domain_scores_gemma":[0.9998271,0.00001882487,0.0000273413,0.00002558277,0.00008868871,0.00001260841],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003262342,0.0002234139,0.03845321,0.0004062619,0.0001462773,0.0003466558,0.0003647707,0.03333861,0.06860042,0.002215035,0.01169059,0.8438886],"study_design_scores_gemma":[0.00003040288,0.0003205514,0.3795508,0.0001641883,0.000209931,0.0009172629,0.001807201,0.521108,0.05984562,0.003605819,0.03236451,0.00007573251],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7738405,0.002007787,0.1836771,0.0006350006,0.0002331669,0.0007836155,0.00978756,0.002465559,0.02656966],"genre_scores_gemma":[0.8308017,0.0008164555,0.1527822,0.000101975,0.00004312707,0.0001341465,0.00961946,0.00005308025,0.005647877],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01679204,"threshold_uncertainty_score":0.03338856,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01116160511542641,"score_gpt":0.2054233810664855,"score_spread":0.1942617759510591,"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."}}