{"id":"W4385473839","doi":"10.1145/3586183.3606716","title":"RealityCanvas: Augmented Reality Sketching for Embedded and Responsive Scribble Animation Effects","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Augmented Reality Applications","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Mitacs","keywords":"Animation; Computer science; Computer facial animation; Computer animation; Computer graphics (images); Skeletal animation; Human–computer interaction; Motion (physics); Flexibility (engineering); Augmented reality; Action (physics); Character animation; Storytelling; Multimedia; Set (abstract data type); Artificial intelligence; Programming language","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":[0.0006465886,0.001333218,0.0004801313,0.0008024815,0.0004067332,0.001750363,0.00161746,0.001031274,0.02248242],"category_scores_gemma":[0.00275138,0.0007087364,0.0009155775,0.0004355359,0.0007915025,0.001487125,0.001836697,0.001191464,0.003864198],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002138849,"about_ca_system_score_gemma":0.000346039,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000544262,"about_ca_topic_score_gemma":0.0009923778,"domain_scores_codex":[0.9992136,0.0001543194,0.00004528879,0.0001315975,0.0003842903,0.00007094314],"domain_scores_gemma":[0.9988502,0.0005032636,0.00008610544,0.0003652245,0.0001223278,0.00007284578],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004797142,0.0002404302,0.0008840755,0.001896699,0.0001314421,0.001974487,0.004170969,0.02828506,0.4371089,0.05902288,0.01411177,0.4516935],"study_design_scores_gemma":[0.0002590292,0.0006957654,0.002489143,0.000334371,0.0001351519,0.004226209,0.0006793556,0.08658833,0.3407919,0.01025928,0.553136,0.0004055198],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02303907,0.0009610693,0.9474576,0.0001534336,0.0001987092,0.0002248093,0.0003480394,0.0109849,0.01663254],"genre_scores_gemma":[0.2107361,0.001431122,0.7641335,0.000137616,0.00008356192,0.0003986152,0.0008039395,0.002635743,0.01963979],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02248242,"threshold_uncertainty_score":0.07521123,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06944261624052124,"score_gpt":0.3468697215788637,"score_spread":0.2774271053383425,"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."}}