{"id":"W4299364625","doi":"","title":"Subpixel image registration for coherent change detection between two high resolution sonar passes","year":2012,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Underwater Acoustics Research","field":"Earth and Planetary Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Subpixel rendering; Image registration; Computer science; Computer vision; Artificial intelligence; Remote sensing; Image resolution; Change detection; Image processing; Image (mathematics); Geology; Pixel","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.005810216,0.0003497187,0.0003653872,0.0002497747,0.0005978931,0.000602901,0.0008532461,0.0003428718,0.0003501305],"category_scores_gemma":[0.0005212439,0.0003586767,0.000158947,0.0002943324,0.0002460907,0.0004242893,0.0002650029,0.000654266,0.0001086879],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001010621,"about_ca_system_score_gemma":0.0002001667,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.03051094,"about_ca_topic_score_gemma":0.0420851,"domain_scores_codex":[0.9942679,0.003079142,0.0005477109,0.0007601397,0.0006879393,0.0006571319],"domain_scores_gemma":[0.9949415,0.001555995,0.000506008,0.001169603,0.001538954,0.0002879116],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.000193425,0.0006636732,0.1154339,0.001611999,0.0003524986,0.000007949312,0.009146724,0.001383366,0.0130691,0.002620143,0.001513475,0.8540037],"study_design_scores_gemma":[0.002358842,0.000009780604,0.5000009,0.001650513,0.0004104178,0.00002154942,0.0002420237,0.3411235,0.1060997,0.02076678,0.02537065,0.001945337],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1524679,0.0008722118,0.8326607,0.004464677,0.0004788915,0.001946096,0.001208975,0.0002740618,0.005626506],"genre_scores_gemma":[0.9345914,0.0003218856,0.05702265,0.00002908672,0.0002985018,0.0001099015,0.006556472,0.00002668187,0.001043477],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8520584,"threshold_uncertainty_score":0.9998865,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05497118534624013,"score_gpt":0.2730463652420232,"score_spread":0.2180751798957831,"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."}}