{"id":"W2155222981","doi":"10.2312/egp.20031032","title":"Curve Synthesis from Learned Refinement Models","year":2003,"lang":"en","type":"article","venue":"","topic":"Human Motion and Animation","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Context (archaeology); Artificial intelligence; Learning curve; Curve fitting; Class (philosophy); Algorithm; Machine learning","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":[0.0005953372,0.0008673936,0.0007949626,0.0009340068,0.0002754692,0.000799912,0.001229564,0.001029323,0.003937047],"category_scores_gemma":[0.002985728,0.0007237211,0.001195924,0.0006127662,0.0005640905,0.001260227,0.00100696,0.001051173,0.001402644],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006946076,"about_ca_system_score_gemma":0.0006508206,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003118059,"about_ca_topic_score_gemma":0.004606841,"domain_scores_codex":[0.9995192,0.00007108609,0.00002273378,0.0001507967,0.0001970853,0.00003908525],"domain_scores_gemma":[0.9991265,0.0003312533,0.00008984623,0.0002379325,0.0001742947,0.00004021596],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001160069,0.00003050037,0.0007896681,0.0001131516,0.00005314821,0.0001742703,0.0001197319,0.7184209,0.025109,0.01135891,0.002087948,0.2416268],"study_design_scores_gemma":[0.000008603682,0.00001848336,0.00009851651,0.000007440506,0.000007795657,0.00004751737,0.000005868577,0.9877788,0.006078719,0.00387997,0.002060094,0.00000815163],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.009911946,0.0001086318,0.9862356,0.00005100021,0.00001766662,0.00003909572,0.00008847507,0.001882987,0.001664673],"genre_scores_gemma":[0.3748457,0.0004510994,0.6160733,0.0001042403,0.00004498544,0.0002124861,0.0008098333,0.0006582074,0.006800241],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003937047,"threshold_uncertainty_score":0.01317072,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04078706150057387,"score_gpt":0.2182939007564375,"score_spread":0.1775068392558636,"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."}}