{"id":"W4400086219","doi":"10.3390/rs16132349","title":"Variational-Based Spatial–Temporal Approximation of Images in Remote Sensing","year":2024,"lang":"en","type":"article","venue":"Remote Sensing","topic":"Advanced Image Fusion Techniques","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Remote sensing; Mean squared error; Poisson distribution; Pixel; Metric (unit); Satellite; Image resolution; Artificial intelligence; Algorithm; Pattern recognition (psychology); Mathematics; Statistics; Geography","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":[0.0003002697,0.0001823835,0.0002357198,0.0004047047,0.00003036569,0.00004592555,0.00005119881,0.0001005881,0.000008505678],"category_scores_gemma":[0.0001273202,0.0002046441,0.00006773386,0.0004648071,0.00003582456,0.000184209,0.0000238075,0.0002442146,0.00000916983],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001895913,"about_ca_system_score_gemma":0.00004983063,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004911465,"about_ca_topic_score_gemma":0.00006254013,"domain_scores_codex":[0.9988363,0.00005339848,0.0004247614,0.0002348451,0.0002323681,0.0002183626],"domain_scores_gemma":[0.9994392,0.00014803,0.0000563317,0.0002389759,0.00008028455,0.00003713662],"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":[0.000006064287,0.000001993965,0.000001572387,0.000272116,0.000007914144,0.0000608513,0.000135025,0.02710458,0.2562429,0.00001318752,0.00008976459,0.716064],"study_design_scores_gemma":[0.0001029055,0.000007941399,0.00003698938,0.0006413282,0.000008185613,0.00001905358,0.00001508453,0.7794053,0.2160648,0.003222043,0.00032508,0.0001513103],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01580361,0.0002707746,0.9807509,0.0001408342,0.0002731038,0.0002096941,0.000005831201,0.000896725,0.001648559],"genre_scores_gemma":[0.5115857,0.00001594601,0.4882357,0.00001920397,0.00006205747,3.990806e-9,0.00001930489,0.00004360657,0.00001851962],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7523007,"threshold_uncertainty_score":0.8345144,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009292646416853751,"score_gpt":0.2460023422888687,"score_spread":0.2367096958720149,"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."}}