{"id":"W2161096037","doi":"10.1002/cav.88","title":"Interactive venation‐based leaf shape modeling","year":2005,"lang":"en","type":"article","venue":"Computer Animation and Virtual Worlds","topic":"Computer Graphics and Visualization Techniques","field":"Computer Science","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Representation (politics); Lamina; Polygon mesh; Topological skeleton; Surface (topology); Interpolation (computer graphics); Skeleton (computer programming); Tree (set theory); Biological system; Triangle mesh; Artificial intelligence; Computer vision; Geometry; Computer graphics (images); Anatomy; Biology; Mathematics; Image (mathematics); Segmentation; Mathematical analysis; Active shape model","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002284332,0.0001673069,0.0001564152,0.0003815745,0.0001903577,0.0004403906,0.0003998575,0.00005508991,0.00002952704],"category_scores_gemma":[0.000008400076,0.0001694447,0.00006248543,0.0004628407,0.00002640513,0.000961094,0.0002459774,0.0001313735,0.0000219866],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004098277,"about_ca_system_score_gemma":0.00003429739,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003229019,"about_ca_topic_score_gemma":0.000005220008,"domain_scores_codex":[0.9988296,0.00006723606,0.00030851,0.0003877922,0.0002332284,0.0001736218],"domain_scores_gemma":[0.9992844,0.00007444657,0.00009500785,0.0002680057,0.0001818335,0.0000963337],"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":[0.00000893824,0.0001216037,0.00008817987,0.00001108563,0.00001555775,0.000001421151,0.001104016,0.007202908,0.00009365463,0.5842535,0.0016846,0.4054145],"study_design_scores_gemma":[0.0003258524,0.0001426351,0.0004164033,0.00004114375,0.000003315693,0.000004953909,0.000008020498,0.9921483,0.0003798846,0.001467363,0.004858749,0.0002034238],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01235954,0.00005138258,0.9853405,0.001057667,0.000189537,0.000138897,0.000001415664,0.0004894088,0.0003716028],"genre_scores_gemma":[0.8989149,0.00001520497,0.09865808,0.00212669,0.0001929663,0.00001240353,0.00001294396,0.00001059971,0.00005616173],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9849454,"threshold_uncertainty_score":0.6909752,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02441262318166891,"score_gpt":0.2966076515685221,"score_spread":0.2721950283868532,"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."}}