{"id":"W2980895755","doi":"10.1145/3332165.3347872","title":"Loki","year":2019,"lang":"en","type":"article","venue":"","topic":"Augmented Reality Applications","field":"Computer Science","cited_by":160,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Autodesk (Canada)","funders":"","keywords":"Computer science; Asynchronous communication; Interactivity; Human–computer interaction; Variety (cybernetics); Context (archaeology); Set (abstract data type); Multimedia; Presentation (obstetrics); Virtual reality; Space (punctuation); Spatial contextual awareness; Physical space; Artificial intelligence; Telecommunications","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":[0.0009674186,0.00076495,0.0004421146,0.001261256,0.001195382,0.002635435,0.001649106,0.0013491,0.2311804],"category_scores_gemma":[0.002942559,0.0004654108,0.0004943932,0.0006893448,0.0006220206,0.003233691,0.003685436,0.001155921,0.1365115],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007084288,"about_ca_system_score_gemma":0.001457067,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001843478,"about_ca_topic_score_gemma":0.004439498,"domain_scores_codex":[0.9993145,0.00009020608,0.00004406825,0.0001830984,0.0002844041,0.00008368605],"domain_scores_gemma":[0.9986826,0.000225139,0.00008304237,0.0003710562,0.0003781542,0.0002600523],"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":[0.0009992823,0.0003432695,0.002425397,0.001600097,0.00004141069,0.0005168269,0.001623015,0.000913196,0.0350611,0.03980463,0.3973595,0.5193124],"study_design_scores_gemma":[0.00006903594,0.0001339427,0.001624262,0.000130716,0.00002193114,0.0005609086,0.0002339169,0.001983603,0.004640445,0.003426922,0.987123,0.00005123959],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.01813006,0.001574309,0.1425313,0.002949665,0.001161928,0.001238813,0.008978217,0.06709574,0.7563399],"genre_scores_gemma":[0.09259047,0.001547507,0.1161899,0.002253692,0.0002677652,0.001477066,0.01456531,0.006448968,0.7646594],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.2311804,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005343498594254954,"score_gpt":0.2144156838285441,"score_spread":0.2090721852342892,"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."}}