{"id":"W33961824","doi":"10.1016/j.envres.2021.111205","title":"Change Detection Methods for Hyperspectral Imagery","year":2007,"lang":"en","type":"article","venue":"Environmental Research","topic":"Remote-Sensing Image Classification","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Institutes of Health Research","keywords":"Hyperspectral imaging; Remote sensing; Change detection; Artificial intelligence; Computer science; Computer vision; Environmental science; Geography","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001876571,0.00009271649,0.00008254886,0.0001898087,0.000126226,0.0000330254,0.00009867539,0.00008060788,0.00003917075],"category_scores_gemma":[0.0001016778,0.0001014613,0.00005125717,0.0001621556,0.0001207528,0.0001572814,0.00003030553,0.0002729293,0.0001449634],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005717754,"about_ca_system_score_gemma":0.000003286281,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007764928,"about_ca_topic_score_gemma":0.000004989163,"domain_scores_codex":[0.998886,0.00007178818,0.0001381161,0.0002013225,0.000236222,0.0004664942],"domain_scores_gemma":[0.9993106,0.0003450058,0.00001146894,0.0002292184,0.000008969894,0.00009471465],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00001175135,0.00001288691,0.0000493216,0.000008710095,0.00000487452,0.000001691359,0.0001089654,0.000007842747,0.5898012,0.000004882064,0.00002351806,0.4099644],"study_design_scores_gemma":[0.0002124382,0.00007237845,0.04696015,0.000006552898,0.000004591404,0.0000127124,0.0003561458,0.02988551,0.9096496,0.0004631561,0.01223416,0.0001426762],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.472499,0.0006851853,0.5229883,0.0000934234,0.0003299548,0.0007098765,0.000005519125,0.0001695556,0.002519227],"genre_scores_gemma":[0.9297714,0.0001136574,0.06935766,0.00001104079,0.0003010903,0.00003461059,0.00001156991,0.00005086445,0.0003481232],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4572724,"threshold_uncertainty_score":0.413747,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1197832351016159,"score_gpt":0.40825681106739,"score_spread":0.2884735759657741,"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."}}