{"id":"W2153285743","doi":"10.1109/robot.1994.351217","title":"Reciprocal-wedge transform in motion stereo","year":2002,"lang":"en","type":"article","venue":"","topic":"Image and Object Detection Techniques","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Epipolar geometry; Computer vision; Artificial intelligence; Computer science; Mathematics; Image (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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001156864,0.00006004531,0.0000642973,0.0001398858,0.00003205107,0.00005723504,0.0002311954,0.00004293356,0.0001698494],"category_scores_gemma":[0.000006001893,0.00005240537,0.00003049671,0.0003489086,0.000009700429,0.0005762742,0.00002185899,0.00008441721,0.000162937],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003859966,"about_ca_system_score_gemma":0.000002865547,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004390475,"about_ca_topic_score_gemma":0.0000464652,"domain_scores_codex":[0.9994504,0.00001881907,0.0001307639,0.0001654675,0.0000949142,0.0001395669],"domain_scores_gemma":[0.9997318,0.00001115123,0.00001409102,0.000196558,0.00001962988,0.00002681554],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[8.739918e-7,0.00004231404,0.00002924161,0.000003978171,8.075202e-7,0.000006937272,0.0004013307,6.113272e-7,0.0004064484,0.001453065,0.001475777,0.9961786],"study_design_scores_gemma":[0.0005056513,0.0001836738,0.001309842,0.00001941498,0.000001434065,0.00003652209,0.00003740254,0.05384379,0.9142643,0.01051244,0.0190025,0.0002830015],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001346416,0.0000325067,0.8968287,0.0007353291,0.00008438107,0.0001211942,1.099333e-7,0.0004101569,0.1004412],"genre_scores_gemma":[0.9774606,0.00003812482,0.01776964,0.0005464604,0.00002226197,0.00002192847,1.76376e-7,0.000004109701,0.004136697],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9958956,"threshold_uncertainty_score":0.2137029,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01895220305267826,"score_gpt":0.2267747795680391,"score_spread":0.2078225765153608,"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."}}