{"id":"W2059403017","doi":"10.1006/cviu.2002.0970","title":"Range Flow Estimation","year":2002,"lang":"en","type":"article","venue":"Computer Vision and Image Understanding","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":65,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"","keywords":"Regularization (linguistics); Computation; Algorithm; Range (aeronautics); Grid; Computer science; Constraint (computer-aided design); Optical flow; Mathematics; Vector field; Motion estimation; Displacement field; Flow (mathematics); Displacement (psychology); Least-squares function approximation; Mathematical optimization; Artificial intelligence; Image (mathematics); Geometry","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":[0.0001610094,0.0001683602,0.000165148,0.0001900571,0.0003427005,0.0006094815,0.000292017,0.00003703055,0.00007733397],"category_scores_gemma":[0.00001818694,0.0001470309,0.00005164749,0.0002854335,0.00007119672,0.001781877,0.0002942978,0.0001320287,0.00008959819],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008595474,"about_ca_system_score_gemma":0.00000440937,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":6.885189e-7,"about_ca_topic_score_gemma":2.014429e-7,"domain_scores_codex":[0.9988362,0.00004681963,0.0002084737,0.0004166202,0.0002267817,0.0002651719],"domain_scores_gemma":[0.9993411,0.00009519869,0.0000654605,0.0003206257,0.00003430272,0.0001433027],"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":[0.000003998889,0.00005044142,0.00002964966,0.00002333869,0.000007323622,0.0000412625,0.0009548811,0.0001373039,0.0005792077,0.02375917,0.01250528,0.9619082],"study_design_scores_gemma":[0.0005833238,0.00008400752,0.00009882348,0.00007229139,0.000002621435,0.00006030906,0.00004129844,0.9868557,0.00007412556,0.01023211,0.001704191,0.000191238],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0001334922,0.0002623853,0.9944172,0.001902216,0.0003894708,0.0001045931,6.310123e-7,0.0002773915,0.002512634],"genre_scores_gemma":[0.2075865,0.0001122038,0.7911726,0.000921366,0.00006475601,0.000001604208,0.000001284292,0.00001143349,0.0001282647],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9867184,"threshold_uncertainty_score":0.5995746,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04409873601557305,"score_gpt":0.2770092737312213,"score_spread":0.2329105377156482,"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."}}