{"id":"W2884910046","doi":"10.1109/tvcg.2018.2860016","title":"Model-Guided 3D Sketching","year":2018,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Computer Graphics and Visualization Techniques","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Guangdong Science and Technology Department; National Natural Science Foundation of China","keywords":"Computer science; Workflow; Human–computer interaction; Interface (matter); 3D modeling; Set (abstract data type); 3d model; User interface; Computer graphics (images); Artificial intelligence; Programming language","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":[0.0007996552,0.001807808,0.001029974,0.001137363,0.0004149958,0.002238143,0.002811655,0.001572113,0.01632971],"category_scores_gemma":[0.005023361,0.00106119,0.001546434,0.0006790978,0.0007478352,0.002641153,0.004720224,0.001735424,0.004718747],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002959326,"about_ca_system_score_gemma":0.0006036449,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001052302,"about_ca_topic_score_gemma":0.001622956,"domain_scores_codex":[0.9990808,0.0001642642,0.00006322889,0.0001782491,0.0004593422,0.00005411927],"domain_scores_gemma":[0.9976594,0.0008780432,0.0001337661,0.0008745446,0.0003010019,0.0001531351],"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":[0.0003804659,0.0001889705,0.001549965,0.00133604,0.0001411285,0.0009832808,0.002303227,0.05521145,0.1299923,0.03319509,0.02902854,0.7456896],"study_design_scores_gemma":[0.0001555538,0.0002719695,0.001095386,0.0002609372,0.00009486369,0.002024128,0.0003704505,0.6477693,0.1055037,0.02861149,0.2135787,0.0002634198],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00316131,0.0001689855,0.9835053,0.00007194839,0.00004804497,0.00005980925,0.0001743588,0.01063465,0.00217563],"genre_scores_gemma":[0.09020361,0.000519325,0.9007714,0.0001686045,0.00003824566,0.0001813283,0.0007366672,0.001836561,0.005544307],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01632971,"threshold_uncertainty_score":0.05462831,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03847285506193231,"score_gpt":0.3154578790244135,"score_spread":0.2769850239624812,"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."}}