{"id":"W4297123695","doi":"10.32920/ryerson.14663097","title":"DirectAR: Marketing an Educative AR Experience in 2019","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Augmented Reality Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Videography; Product (mathematics); Marketing; Advertising; Business; Public relations; Political science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009563236,0.0002125082,0.0002273681,0.0002022803,0.0001554098,0.0001685605,0.002838271,0.00009666477,0.0005514075],"category_scores_gemma":[0.00009103765,0.0002262782,0.00006265153,0.0005095139,0.00006153975,0.000284473,0.004353701,0.0007210569,0.00003244965],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003583409,"about_ca_system_score_gemma":0.0003920573,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001902716,"about_ca_topic_score_gemma":0.0001744191,"domain_scores_codex":[0.9974253,0.0004785069,0.0003608118,0.001074269,0.0003559156,0.0003051567],"domain_scores_gemma":[0.9976165,0.0002431579,0.000201296,0.001775588,0.00005108877,0.0001123687],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007337851,0.005277396,0.01941995,0.0003736942,0.0001832317,0.00008227894,0.2364164,0.04193341,0.001758766,0.329207,0.04444673,0.3208277],"study_design_scores_gemma":[0.0008482898,0.0001641752,0.221651,0.0004309035,0.0000309147,0.00004966799,0.02635789,0.5756634,0.003099273,0.05092457,0.116334,0.004445809],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1359883,0.0004469892,0.7148163,0.006753436,0.001870055,0.002037083,0.00005122658,0.0009511677,0.1370855],"genre_scores_gemma":[0.8025046,0.0002604045,0.1814784,0.001280192,0.0001982989,0.004401989,0.0002205359,0.00005375479,0.00960183],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6665163,"threshold_uncertainty_score":0.9227356,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03962616561623621,"score_gpt":0.348483739722671,"score_spread":0.3088575741064348,"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."}}