{"id":"W3195572326","doi":"10.1007/978-3-030-85613-7_1","title":"Diegetic and Non-diegetic Health Interfaces in VR Shooter Games","year":2021,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Virtual Reality Applications and Impacts","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Computer graphics (images); Human–computer interaction","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008645913,0.0004650137,0.0006577093,0.0007294676,0.0001765715,0.0007332442,0.00184146,0.0002216449,0.00001302814],"category_scores_gemma":[0.00008991257,0.0004225159,0.0000680624,0.0007020455,0.0006051883,0.0005222564,0.001589076,0.0007646257,0.00001881381],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003291428,"about_ca_system_score_gemma":0.0007656204,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001648198,"about_ca_topic_score_gemma":0.0006466944,"domain_scores_codex":[0.9964485,0.00005125545,0.0006165199,0.001538307,0.0006205445,0.0007248462],"domain_scores_gemma":[0.9977497,0.0003425771,0.0002380131,0.001266779,0.0001226852,0.0002801821],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000002603049,0.00004672909,0.00008108583,0.00009261703,0.000006826407,0.00004108659,0.002688815,0.002124083,0.0001376211,0.01422142,0.00003172042,0.9805254],"study_design_scores_gemma":[0.001201139,0.001278116,0.01016254,0.004940765,0.00001513807,0.0003581157,0.000007190216,0.6832459,0.003294474,0.283825,0.009052053,0.002619588],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001803419,0.002233889,0.989081,0.004217238,0.0004949765,0.0004251132,0.000005172914,0.00005883916,0.001680348],"genre_scores_gemma":[0.8837832,0.0005656336,0.1114152,0.00374094,0.0001507063,0.00001786852,0.000005325578,0.00002938342,0.0002917716],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9779058,"threshold_uncertainty_score":0.9998227,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01951275519665224,"score_gpt":0.2773068480045774,"score_spread":0.2577940928079251,"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."}}