{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004478524,0.0003560412,0.0003944882,0.002155569,0.0001566117,0.0007408938,0.0002112324,0.0002926541,0.0005429803],"category_scores_gemma":[0.001148489,0.0002120701,0.0004048354,0.001556826,0.0003682451,0.0009859124,0.0004425078,0.0003272091,0.0001553207],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002282027,"about_ca_system_score_gemma":0.0002175158,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001241926,"about_ca_topic_score_gemma":0.002127168,"domain_scores_codex":[0.9996209,0.00008504035,0.00001395658,0.00006036806,0.0001756542,0.00004410851],"domain_scores_gemma":[0.9995257,0.0001244924,0.0001039062,0.00006729588,0.0001489848,0.00002973914],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005960896,0.0001763912,0.03489584,0.0002799638,0.0001691216,0.0003063006,0.000184602,0.04608603,0.3375571,0.004174324,0.0009528393,0.5746214],"study_design_scores_gemma":[0.00002949346,0.0002294439,0.07311147,0.00002662874,0.0001918853,0.0005949818,0.0001694587,0.8425314,0.07693538,0.00278183,0.003316253,0.0000818141],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4749416,0.0004978181,0.5195885,0.0002307246,0.00008082608,0.00005402545,0.0001988138,0.00063335,0.003774184],"genre_scores_gemma":[0.9111676,0.0002318375,0.08767408,0.00003726529,0.00004660583,0.0000228084,0.0001507007,0.00004161063,0.0006274944],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002155569,"threshold_uncertainty_score":0.002469361,"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."}}