{"id":"W1969076082","doi":"10.1111/j.1467-8659.2008.01283.x","title":"Deformation‐Driven Shape Correspondence","year":2008,"lang":"en","type":"article","venue":"Computer Graphics Forum","topic":"3D Shape Modeling and Analysis","field":"Engineering","cited_by":168,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Simon Fraser University","funders":"","keywords":"Polygon mesh; Computer science; Tree traversal; Shape analysis (program analysis); Deformation (meteorology); Distortion (music); Artificial intelligence; Matching (statistics); Correspondence problem; Free-form deformation; Feature (linguistics); Scale (ratio); Algorithm; Computer vision; Mathematics; Computer graphics (images)","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":[0.0006247468,0.0006405233,0.0007629135,0.001275149,0.0007254502,0.001199387,0.001733072,0.001335443,0.00551481],"category_scores_gemma":[0.002013834,0.0005944006,0.0008188827,0.001294717,0.001052809,0.001318586,0.002420706,0.0009334868,0.002129306],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006865734,"about_ca_system_score_gemma":0.0007500101,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009120053,"about_ca_topic_score_gemma":0.001123964,"domain_scores_codex":[0.9989493,0.0001393394,0.00004335975,0.0002193719,0.0005699361,0.00007864634],"domain_scores_gemma":[0.9989225,0.0002549692,0.0001166439,0.000462227,0.0001888051,0.00005480479],"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":[0.0003385494,0.0001704743,0.001911125,0.0001746123,0.0000803111,0.0003129503,0.0002584603,0.3907617,0.1127936,0.05901095,0.007351798,0.4268355],"study_design_scores_gemma":[0.00002007472,0.00007622518,0.0006132221,0.00001005261,0.000008705276,0.0003609295,0.00004210678,0.9394727,0.03219741,0.02011272,0.007055327,0.00003046456],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02903926,0.0001135193,0.9637057,0.0001025609,0.00005508662,0.00007831987,0.00007631584,0.001471955,0.005357378],"genre_scores_gemma":[0.526714,0.0001479408,0.4636434,0.0001574174,0.00004323112,0.000130158,0.0003752052,0.0006894456,0.008099129],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00551481,"threshold_uncertainty_score":0.01844883,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01542678953748521,"score_gpt":0.1996035401021281,"score_spread":0.1841767505646428,"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."}}