{"id":"W2156074549","doi":"10.1109/tpami.2011.24","title":"Dynamic Refraction Stereo","year":2011,"lang":"en","type":"article","venue":"IEEE Transactions on Pattern Analysis and Machine Intelligence","topic":"Computer Graphics and Visualization Techniques","field":"Computer Science","cited_by":75,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Morgan Solar (Canada)","funders":"Natural Sciences and Engineering Research Council of Canada; Alfred P. Sloan Foundation","keywords":"Computer vision; Refraction; Computer science; Artificial intelligence; Position (finance); Point (geometry); Surface reconstruction; Surface (topology); Refractive index; Matching (statistics); Optics; Stereopsis; Mathematics; Geometry; Physics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001859426,0.0001746495,0.0002088548,0.0007569796,0.0001668364,0.0001147214,0.0004087792,0.00005976185,0.0001285198],"category_scores_gemma":[0.000001085059,0.0001574197,0.0001880467,0.001208042,0.00004001734,0.0003050202,0.000007386044,0.0001827824,0.00001663741],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002101035,"about_ca_system_score_gemma":0.000009817611,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007863057,"about_ca_topic_score_gemma":0.0007310403,"domain_scores_codex":[0.9988062,0.00006643327,0.000313388,0.0004595245,0.0001890093,0.000165476],"domain_scores_gemma":[0.9991685,0.00004165624,0.0001054052,0.0005089573,0.00007878729,0.00009668314],"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":[0.000006241458,0.0002114769,0.0004904547,0.000009015459,0.0002814347,0.00000631725,0.0006791747,0.0001871517,0.00007123304,0.002885271,0.000005107299,0.9951671],"study_design_scores_gemma":[0.00006407664,0.0002606899,0.003546076,0.00002010573,0.0002333813,0.00001441653,0.00002705897,0.8913985,0.1008395,0.00312031,0.0001328649,0.000342981],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001742933,0.00004291128,0.9975051,0.00006550775,0.0001713371,0.00008826137,0.00000851884,0.0002229978,0.0001523811],"genre_scores_gemma":[0.9929194,0.0004805573,0.006115214,0.0003372243,0.00000451085,0.00001697618,0.000002672269,0.000008579354,0.0001149082],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9948241,"threshold_uncertainty_score":0.641939,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03024970903920304,"score_gpt":0.2954016865515515,"score_spread":0.2651519775123485,"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."}}