{"id":"W4403331717","doi":"10.23919/fusion59988.2024.10706502","title":"Leveraging Generative Deep Learning Models for Enhanced Change Detection in Heterogeneous Remote Sensing Data","year":2024,"lang":"en","type":"article","venue":"","topic":"Remote-Sensing Image Classification","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Space Agency","keywords":"Computer science; Generative grammar; Change detection; Generative model; Deep learning; Data modeling; Artificial intelligence; Remote sensing; Machine learning; Data science; Geography; Database","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000252671,0.000173622,0.0001545402,0.0002110496,0.00007430536,0.0001615043,0.0001022179,0.00008906305,0.000002938255],"category_scores_gemma":[0.00005773432,0.0001890359,0.00003635256,0.000277726,0.00001396003,0.0005471694,0.00004807224,0.0002295544,0.00001444125],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001857566,"about_ca_system_score_gemma":0.000009668916,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007268214,"about_ca_topic_score_gemma":0.0003925265,"domain_scores_codex":[0.9988945,0.00004283216,0.000239967,0.0004357981,0.0001083845,0.000278524],"domain_scores_gemma":[0.9994419,0.0001007979,0.00002115825,0.0003542718,0.00004365534,0.00003826153],"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":[0.000003562413,9.466243e-7,1.102119e-7,0.00005791062,0.00001445179,0.000007225779,0.0008846987,0.2434657,0.2335926,0.000003067087,0.000004028932,0.5219657],"study_design_scores_gemma":[0.00009519504,0.00001081815,0.000005641741,0.00008601003,0.00001112253,0.00002306795,0.00008486,0.7949628,0.2038644,0.0003172242,0.0003727466,0.0001660958],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06478727,0.000649426,0.932384,0.00006418281,0.0005141336,0.0003515737,0.000002410322,0.0007591893,0.0004878813],"genre_scores_gemma":[0.924618,0.0001127592,0.0747458,0.00002849039,0.0002512122,0.000001989982,0.00006517398,0.00007955336,0.00009702156],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8598307,"threshold_uncertainty_score":0.7708659,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1077859149712707,"score_gpt":0.2840511133610563,"score_spread":0.1762651983897856,"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."}}