{"id":"W2380707673","doi":"10.6046/gtzyyg.2009.03.07","title":"REMOTE SENSING CHANGE DETECTION BY INCLUSION OF MULTITEMPORAL TEXTURE","year":2009,"lang":"en","type":"article","venue":"Guotu ziyuan yaogan","topic":"Remote-Sensing Image Classification","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Change detection; Variogram; Remote sensing; Texture (cosmology); Computer science; Pattern recognition (psychology); Artificial intelligence; Geology; Kriging; Image (mathematics)","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":[0.0001645204,0.0001850658,0.0002063811,0.0001538893,0.000140261,0.00002502384,0.0001050187,0.0001788646,0.000004145329],"category_scores_gemma":[0.00005593396,0.0002059369,0.00006598532,0.0003547371,0.00003500737,0.000210327,0.0000491812,0.0002152423,0.0000194623],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001346885,"about_ca_system_score_gemma":0.000006020763,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001056257,"about_ca_topic_score_gemma":0.00004652746,"domain_scores_codex":[0.998972,0.0000367121,0.0002944939,0.0002219988,0.000234323,0.0002405002],"domain_scores_gemma":[0.9993641,0.00002221929,0.0000964169,0.0003570556,0.00008340867,0.00007676943],"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":[0.000006555063,0.000005988986,0.000008175491,0.00001751398,0.000004181412,0.000003055343,0.0004557947,0.00004463918,0.5118441,0.000001194691,0.0003133855,0.4872954],"study_design_scores_gemma":[0.0004091628,0.00008334743,0.005192299,0.0001074193,0.00002082141,0.00002727981,0.00005889294,0.541443,0.4412391,0.0002583755,0.01085698,0.0003033244],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8234802,0.0006282749,0.1683814,0.0007824608,0.0008237688,0.0005652778,0.00001590318,0.001076743,0.004245979],"genre_scores_gemma":[0.9894089,0.00003770515,0.01010179,0.0001094447,0.0001993931,1.253223e-7,0.00003681277,0.00004032795,0.00006557189],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5413983,"threshold_uncertainty_score":0.8397865,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01719543435558524,"score_gpt":0.231563703009931,"score_spread":0.2143682686543457,"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."}}