{"id":"W2082812585","doi":"10.1145/1377980.1377995","title":"Non-linear perspective widgets for creating multiple-view images","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"National Science Foundation","keywords":"Computer science; Perspective (graphical); Variety (cybernetics); Set (abstract data type); Projection (relational algebra); Object (grammar); Human–computer interaction; Range (aeronautics); Visualization; Computer graphics (images); Theoretical computer science; Artificial intelligence; Algorithm; Programming language","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":[0.001805171,0.001877177,0.0009363163,0.00116389,0.0005017673,0.00190364,0.002822586,0.001031407,0.01496309],"category_scores_gemma":[0.007520152,0.0008794001,0.001715051,0.000693095,0.0006525235,0.00284163,0.005539019,0.001585487,0.00348929],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002303413,"about_ca_system_score_gemma":0.0002489504,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003334018,"about_ca_topic_score_gemma":0.00105814,"domain_scores_codex":[0.9992255,0.0001551447,0.0000933301,0.0001490967,0.0002758573,0.0001010453],"domain_scores_gemma":[0.9963981,0.001778631,0.0001748646,0.001106436,0.0002965902,0.000245353],"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":[0.001741601,0.000330642,0.004442171,0.001496475,0.0003069347,0.001534269,0.001984008,0.01405633,0.1210771,0.08277451,0.05496181,0.7152942],"study_design_scores_gemma":[0.0004520815,0.0008289723,0.005158363,0.0005166455,0.0003403111,0.003763866,0.001114138,0.2839747,0.2689292,0.07769252,0.3566487,0.0005805821],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004922607,0.0001833048,0.9830766,0.00008005276,0.00008004207,0.0001100077,0.0004552228,0.009510609,0.001581711],"genre_scores_gemma":[0.08964384,0.0003702681,0.8990646,0.0002924476,0.0000720187,0.0007089036,0.001452504,0.003667985,0.004727582],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01496309,"threshold_uncertainty_score":0.05005652,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03038667094428494,"score_gpt":0.3268495860452002,"score_spread":0.2964629151009153,"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."}}