{"id":"W2073290147","doi":"10.1145/2601097.2601147","title":"From capture to simulation","year":2014,"lang":"en","type":"article","venue":"ACM Transactions on Graphics","topic":"Computer Graphics and Visualization Techniques","field":"Computer Science","cited_by":84,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Networks of Centres of Excellence of Canada; Natural Sciences and Engineering Research Council of Canada; Deutsche Forschungsgemeinschaft","keywords":"Computer science; Deblurring; Fluid dynamics; Flow (mathematics); Tracking (education); Fluid queue; Operator (biology); Modular design; Algorithm; Computer vision; Artificial intelligence; Computational science; Image (mathematics); Image processing; Mathematics; Image restoration; 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":[0.001054471,0.0008344138,0.0008987906,0.0008294508,0.0009046135,0.004077352,0.00184138,0.001961116,0.0143992],"category_scores_gemma":[0.004774475,0.0008290684,0.00117165,0.0006826405,0.003056823,0.004739688,0.008129825,0.003065879,0.003060984],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00148202,"about_ca_system_score_gemma":0.001450596,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004075627,"about_ca_topic_score_gemma":0.00265648,"domain_scores_codex":[0.9990157,0.0002724734,0.00003857238,0.0002177114,0.0003468715,0.000108659],"domain_scores_gemma":[0.9985661,0.0005684534,0.00007976947,0.0004722074,0.0001813388,0.0001322615],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00012957,0.00005620151,0.001015087,0.0004138547,0.00007941768,0.0002827967,0.0007614499,0.17206,0.007000921,0.7350164,0.01458436,0.06859982],"study_design_scores_gemma":[0.00004080967,0.0000734072,0.000437592,0.0001955061,0.00003436283,0.0002642164,0.0002614577,0.4135903,0.004930313,0.4935006,0.08659982,0.00007159384],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007327607,0.002103415,0.9517483,0.003104748,0.0004715563,0.000118314,0.0003551131,0.001179755,0.03359114],"genre_scores_gemma":[0.4587622,0.01031242,0.4728912,0.00292751,0.0009503246,0.0007159509,0.001508152,0.002567105,0.0493652],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0143992,"threshold_uncertainty_score":0.04817015,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02270619986561468,"score_gpt":0.2973210179069352,"score_spread":0.2746148180413205,"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."}}