{"id":"W4407920545","doi":"10.18280/jesa.580112","title":"Identification and Evaluation of Cybersickness Impact of Mixed Reality Simulator (MRSi) System","year":2025,"lang":"fr","type":"article","venue":"Journal Européen des Systèmes Automatisés","topic":"Simulation and Modeling Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Identification (biology); Computer science; Simulation","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006878164,0.0004521529,0.0003627401,0.0005545047,0.0001758795,0.0004417883,0.0002610671,0.0003681437,0.001967408],"category_scores_gemma":[0.004728286,0.0001375872,0.00037657,0.0001987165,0.0002080647,0.0003953852,0.0005933543,0.0001672579,0.0002423908],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001772001,"about_ca_system_score_gemma":0.0002198573,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007038329,"about_ca_topic_score_gemma":0.0008476292,"domain_scores_codex":[0.9990997,0.000305748,0.00009504769,0.00006807493,0.000351774,0.00007957847],"domain_scores_gemma":[0.9981385,0.0007946424,0.0002543071,0.0001301557,0.0005436935,0.0001386694],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.007786701,0.002005496,0.2724004,0.004472072,0.0006269623,0.002328821,0.006382397,0.02951348,0.445389,0.0005733818,0.001895223,0.226626],"study_design_scores_gemma":[0.0001541773,0.02855253,0.744326,0.0002602834,0.0006804983,0.002596662,0.005894257,0.0571747,0.1547514,0.0002470855,0.005163338,0.0001991232],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9938625,0.0001953808,0.004574076,0.00002567295,0.00001863512,0.00009758213,0.0001539397,0.00007388632,0.0009984227],"genre_scores_gemma":[0.9964115,0.0001417691,0.002634441,0.00001671343,0.00000524304,0.00004906124,0.0001486229,0.00001114141,0.0005815076],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001967408,"threshold_uncertainty_score":0.006581604,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03578321932603667,"score_gpt":0.3315518749679887,"score_spread":0.295768655641952,"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."}}