{"id":"W4312202115","doi":"10.1007/s10055-022-00740-5","title":"Assessment of user-interaction strategies for neurosurgical data navigation and annotation in virtual reality","year":2022,"lang":"en","type":"article","venue":"Virtual Reality","topic":"Augmented Reality Applications","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Human–computer interaction; Virtual reality; Usability; Context (archaeology); 3D interaction; Interaction technique; Modalities; Task (project management); Selection (genetic algorithm); Point (geometry); Annotation; User interface; Artificial intelligence","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":[0.001837044,0.0001303208,0.0002224396,0.0001075008,0.0002331126,0.0001122809,0.0007637613,0.00005120461,0.000006880894],"category_scores_gemma":[0.00008994473,0.0001429391,0.00003794935,0.0004993903,0.00008864503,0.001183494,0.0008210532,0.000268242,4.23576e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001798232,"about_ca_system_score_gemma":0.0002478162,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009214804,"about_ca_topic_score_gemma":0.0001768693,"domain_scores_codex":[0.9976063,0.0004840216,0.0005834825,0.0006618215,0.0004732009,0.0001912109],"domain_scores_gemma":[0.9979658,0.0005112888,0.0003425797,0.00101859,0.00009595852,0.00006582033],"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":[0.00006959911,0.0005790218,0.000845246,0.00004787424,0.00002167602,0.000003278991,0.000592824,0.04759092,0.003916476,0.9193079,0.001005959,0.02601918],"study_design_scores_gemma":[0.000782398,0.0004739889,0.092199,0.00001552045,0.00001492583,0.00001481733,0.001705916,0.8885722,0.0001431382,0.0102919,0.005613457,0.0001728036],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1885609,0.000005016724,0.8079916,0.001511644,0.0001672427,0.0006037786,0.0006692498,0.00006854982,0.000422031],"genre_scores_gemma":[0.9973231,0.00001204247,0.001244566,0.00006654783,0.00002713777,0.0002036514,0.001093526,0.000007947801,0.00002148166],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9090161,"threshold_uncertainty_score":0.5828888,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08639106062015184,"score_gpt":0.3884488474483764,"score_spread":0.3020577868282245,"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."}}