{"id":"W4312879791","doi":"10.1109/ismar-adjunct57072.2022.00156","title":"CARDS: Comprehensive AR Docent System","year":2022,"lang":"en","type":"article","venue":"2022 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)","topic":"Augmented Reality Applications","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"Korea Institute for Advancement of Technology; Ministry of Trade, Industry and Energy","keywords":"Visitor pattern; Exhibition; Augmented reality; Context (archaeology); Computer science; Human–computer interaction; Multimedia; World Wide Web; Visual arts; Art","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":[0.0005747536,0.001354204,0.0007980019,0.00124056,0.0005376488,0.002272799,0.001909651,0.001176939,0.04418105],"category_scores_gemma":[0.001447994,0.0005604925,0.000606145,0.0006899925,0.0004336065,0.001407203,0.002336479,0.0007779585,0.01663191],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005844961,"about_ca_system_score_gemma":0.0006479056,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003369018,"about_ca_topic_score_gemma":0.002734867,"domain_scores_codex":[0.9993801,0.00007358902,0.0000536278,0.0001420828,0.000256272,0.00009436275],"domain_scores_gemma":[0.9995296,0.0000960974,0.0000306762,0.0001411634,0.0001203293,0.00008214788],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.005065492,0.0003717017,0.005670545,0.001441051,0.0002255409,0.001718824,0.001239352,0.005138404,0.07604768,0.01117451,0.4682769,0.42363],"study_design_scores_gemma":[0.0005637816,0.0009571011,0.007253909,0.0001459161,0.0001979374,0.002111985,0.0002892336,0.04718813,0.05232711,0.001683456,0.8869261,0.0003552799],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"software","genre_gemma":"empirical","genre_scores_codex":[0.07133372,0.003074372,0.3844292,0.0007458811,0.0008646883,0.002370659,0.03308027,0.4070523,0.09704898],"genre_scores_gemma":[0.5553946,0.002009732,0.2430873,0.001657529,0.0003560742,0.002444003,0.05664669,0.01026357,0.1281406],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04418105,"threshold_uncertainty_score":0.1478003,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02319849596498548,"score_gpt":0.2616445586834077,"score_spread":0.2384460627184222,"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."}}