{"id":"W2135700807","doi":"10.1145/1572741.1572765","title":"On expert performance in 3D curve-drawing tasks","year":2009,"lang":"en","type":"article","venue":"","topic":"Visual perception and processing mechanisms","field":"Neuroscience","cited_by":65,"is_retracted":false,"has_abstract":true,"ca_institutions":"Autodesk (Canada); University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Sketch; Computer science; Perception; Artificial intelligence; Computer vision; Space (punctuation); Surface (topology); Computer graphics (images); Mathematics; Algorithm; Geometry; Psychology","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":[0.001263924,0.000660467,0.0004149509,0.0006301609,0.0002490114,0.0006254397,0.0003866187,0.0007165195,0.004569754],"category_scores_gemma":[0.0131782,0.0002033897,0.0002303162,0.0002863289,0.0003653933,0.0006850714,0.0005678973,0.0003708809,0.001279622],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002265555,"about_ca_system_score_gemma":0.0001523065,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001635785,"about_ca_topic_score_gemma":0.002210949,"domain_scores_codex":[0.9989512,0.0002387651,0.0001025357,0.0002593947,0.0003349181,0.0001132568],"domain_scores_gemma":[0.9885052,0.007739067,0.00118202,0.001145866,0.0009533011,0.000474574],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.005546845,0.003653429,0.4530807,0.0008095515,0.0003747918,0.003501314,0.0216099,0.009397868,0.1570819,0.0009973744,0.004258351,0.339688],"study_design_scores_gemma":[0.000104615,0.005886204,0.9455554,0.0001059349,0.00009577344,0.003867061,0.004532207,0.01214171,0.02031253,0.00176993,0.005409428,0.0002192059],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9955042,0.00009830159,0.001601625,0.00001338741,0.000008402493,0.00002202664,0.0001001135,0.00003819701,0.00261363],"genre_scores_gemma":[0.9945701,0.0001873646,0.001708828,0.00004528087,0.000007687107,0.00002647792,0.0002715125,0.00001616901,0.003166571],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004569754,"threshold_uncertainty_score":0.0152874,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06949600488774535,"score_gpt":0.3430242176905404,"score_spread":0.273528212802795,"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."}}