{"id":"W4233665685","doi":"10.32920/ryerson.14648931.v1","title":"A markerless augmented reality system for mobile devices","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Augmented Reality Applications","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Augmented reality; Computer science; Computer vision; Rendering (computer graphics); Artificial intelligence; Mobile device; Fiducial marker; Computer graphics (images); Virtual reality; Feature (linguistics)","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":[0.0005380377,0.001354616,0.0009716696,0.0008929984,0.0005456668,0.001686438,0.001755289,0.001372329,0.02172172],"category_scores_gemma":[0.001514204,0.0006872146,0.0006790189,0.0007470253,0.000288211,0.001300186,0.002291524,0.001060239,0.01142821],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002712495,"about_ca_system_score_gemma":0.0004071945,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006158386,"about_ca_topic_score_gemma":0.0006189977,"domain_scores_codex":[0.9989537,0.0001682414,0.00009049467,0.0002100696,0.0005057197,0.00007174581],"domain_scores_gemma":[0.999302,0.00007903454,0.00007077494,0.0002890354,0.0001916832,0.00006743705],"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":[0.001193722,0.0002051431,0.001197262,0.0008806429,0.0001861589,0.001131601,0.00076213,0.004227233,0.2924519,0.01055468,0.07627129,0.6109383],"study_design_scores_gemma":[0.0004807189,0.00154688,0.006379494,0.0002584243,0.000301823,0.006277226,0.0001816654,0.100633,0.193344,0.004747231,0.6853881,0.0004614934],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01413559,0.001228353,0.9186561,0.0001955585,0.0004531833,0.0004735111,0.001732054,0.05106533,0.01206031],"genre_scores_gemma":[0.2977848,0.001738922,0.6451267,0.0005850199,0.0003200406,0.001158228,0.006043282,0.002256695,0.04498619],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02172172,"threshold_uncertainty_score":0.07266641,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03667282033792424,"score_gpt":0.3100670812978058,"score_spread":0.2733942609598816,"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."}}