{"id":"W7143604049","doi":"10.71465/ajainn634","title":"The Role of Deep Learning in Augmented Reality Applications","year":2024,"lang":"","type":"article","venue":"American Journal of Artificial Intelligence and Neural Networks","topic":"Augmented Reality Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Deep learning; Augmented reality; Object (grammar); Key (lock); Natural (archaeology); Visualization","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":[0.0009690514,0.0006955078,0.0003815941,0.0003593742,0.0002519082,0.001482454,0.0007986869,0.0009739599,0.00225129],"category_scores_gemma":[0.003017119,0.0003099721,0.000283079,0.0005072347,0.0007804281,0.002131884,0.001304498,0.001864763,0.0007376679],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005802567,"about_ca_system_score_gemma":0.0004919767,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002643798,"about_ca_topic_score_gemma":0.002802103,"domain_scores_codex":[0.9994312,0.0001680751,0.00002596532,0.0001022375,0.0002187388,0.00005369482],"domain_scores_gemma":[0.9991544,0.000426899,0.00005580911,0.00009756626,0.0002186899,0.00004656053],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001588615,0.0001478276,0.002115472,0.0004102092,0.00009443195,0.0001336819,0.0001595984,0.1785371,0.01681238,0.0651073,0.009042501,0.7272807],"study_design_scores_gemma":[0.000009780439,0.0001041891,0.0009784404,0.0001034393,0.00002521407,0.000105688,0.00005347152,0.9184848,0.008456137,0.05119383,0.02045796,0.00002703517],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.0397132,0.02157373,0.9101197,0.006360418,0.0004070572,0.00003974915,0.0001921717,0.001526513,0.02006746],"genre_scores_gemma":[0.791041,0.01609254,0.180301,0.001131598,0.0003237491,0.00006761693,0.000295418,0.0001544922,0.01059264],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.002643798,"threshold_uncertainty_score":0.007531345,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02273884781760641,"score_gpt":0.2998997447519079,"score_spread":0.2771608969343015,"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."}}