{"id":"W4297156394","doi":"10.1145/3546155.3546642","title":"PONI: A Personalized Onboarding Interface for Getting Inspiration and Learning About AR/VR Creation","year":2022,"lang":"en","type":"article","venue":"","topic":"Augmented Reality Applications","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Onboarding; Computer science; Human–computer interaction; Interface (matter); User interface; Multimedia; Psychology; Programming language; Operating system","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":[0.0009418462,0.001333149,0.0005029876,0.0006986005,0.0003042212,0.001483073,0.001488422,0.001069756,0.02697578],"category_scores_gemma":[0.004626853,0.0003557336,0.0004647052,0.0004089669,0.000374282,0.002291651,0.00267935,0.0008470236,0.0042939],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001823504,"about_ca_system_score_gemma":0.0003533951,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002972301,"about_ca_topic_score_gemma":0.0005945122,"domain_scores_codex":[0.9995807,0.0001097278,0.00002891148,0.000110674,0.0001065229,0.00006339466],"domain_scores_gemma":[0.9977123,0.001392932,0.0001217394,0.0003465696,0.0001470013,0.0002794281],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001674922,0.001231446,0.005728158,0.002347424,0.00009281391,0.00174409,0.0109759,0.002340356,0.1095861,0.006515463,0.07240061,0.7853628],"study_design_scores_gemma":[0.0007714828,0.003644649,0.04744315,0.001258239,0.0003797587,0.00514806,0.0051735,0.04967037,0.08656778,0.01520669,0.7841811,0.0005552809],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1395973,0.001023238,0.754674,0.0008250494,0.0005051932,0.00175953,0.002449958,0.05706203,0.04210363],"genre_scores_gemma":[0.3917477,0.001243921,0.5576411,0.000868272,0.0002393739,0.002168321,0.003607696,0.004540288,0.03794328],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02697578,"threshold_uncertainty_score":0.09024298,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02033312095472266,"score_gpt":0.2895332906928927,"score_spread":0.2692001697381701,"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."}}