{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003920775,0.0005149782,0.0005867279,0.0006303567,0.0003762266,0.001183369,0.000795249,0.0007354348,0.004480668],"category_scores_gemma":[0.001017525,0.0003993888,0.0005894009,0.000531201,0.0005831226,0.001210609,0.001476748,0.0007988681,0.001020726],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007457202,"about_ca_system_score_gemma":0.0008577422,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001888682,"about_ca_topic_score_gemma":0.002761212,"domain_scores_codex":[0.9994307,0.00005325052,0.00001363953,0.0001071904,0.0003458647,0.00004931001],"domain_scores_gemma":[0.9997033,0.00009390948,0.00003216124,0.00007248019,0.00007593556,0.00002216402],"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":[0.0002737683,0.0001038606,0.00201272,0.0002911332,0.0001108942,0.0003352274,0.0003015521,0.1329435,0.1479143,0.204299,0.006398849,0.5050151],"study_design_scores_gemma":[0.00004423193,0.0001141276,0.001496893,0.00004772633,0.00003516569,0.001261801,0.0001297044,0.8597077,0.0580466,0.04949231,0.02956975,0.00005408215],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00743298,0.0002184195,0.9820971,0.0000951556,0.00004572422,0.0000308167,0.00008877026,0.0002743218,0.009716652],"genre_scores_gemma":[0.2420625,0.0008231663,0.7462938,0.000241152,0.0001073737,0.0000750617,0.0005232478,0.0001632434,0.00971046],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004480668,"threshold_uncertainty_score":0.01498932,"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."}}