{"id":"W4252721626","doi":"10.32920/ryerson.14661822.v1","title":"Automatic target matching","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Satellite Image Processing and Photogrammetry","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Artificial intelligence; Subpixel rendering; Computer vision; Epipolar geometry; Computer science; Matching (statistics); Similarity (geometry); Line (geometry); Template matching; Pixel; Image (mathematics); Pattern recognition (psychology); 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":[0.001227226,0.001284687,0.001414004,0.003041216,0.001263188,0.002303304,0.002505247,0.001778841,0.03214682],"category_scores_gemma":[0.003217665,0.0007028098,0.001224092,0.002443698,0.0004902967,0.002272221,0.002369274,0.001028818,0.0183448],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007995619,"about_ca_system_score_gemma":0.001356573,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002665628,"about_ca_topic_score_gemma":0.002129675,"domain_scores_codex":[0.9977692,0.0002346168,0.00009506806,0.0006306819,0.001030557,0.0002399798],"domain_scores_gemma":[0.9986904,0.0002514229,0.00008304247,0.0003594361,0.0005741116,0.00004155869],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003203698,0.0001130654,0.001097506,0.0002106518,0.0000553659,0.0001086185,0.0001555594,0.01827375,0.0620136,0.01254839,0.0184563,0.8866468],"study_design_scores_gemma":[0.0001232146,0.0003591922,0.005961915,0.0000953757,0.00009028957,0.001337437,0.0003457445,0.6480383,0.19168,0.02535936,0.1264621,0.0001470851],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.007348154,0.0001508692,0.9730098,0.00004891293,0.00009408238,0.0001438073,0.000300787,0.009127426,0.00977633],"genre_scores_gemma":[0.1284703,0.0002878155,0.8430791,0.000194987,0.00006865403,0.0003453421,0.003050599,0.002559966,0.02194318],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03214682,"threshold_uncertainty_score":0.1075418,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01163591541313263,"score_gpt":0.2347430769708124,"score_spread":0.2231071615576798,"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."}}