{"id":"W4378213842","doi":"10.32920/23159894.v1","title":"Killing Them Softly: Virtual Reality Training in Project Termination","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Virtual Reality Applications and Impacts","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Mirroring; Virtual reality; Computer science; Training (meteorology); Storytelling; Work (physics); Human–computer interaction; Multimedia; Knowledge management; Psychology; Engineering; Narrative","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":[0.00486496,0.0004744575,0.000306615,0.0006073294,0.001746197,0.003193592,0.001669849,0.001738328,0.01513615],"category_scores_gemma":[0.01223449,0.0003183699,0.000436401,0.000385693,0.001894569,0.002480815,0.005206947,0.001802214,0.003155659],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005908467,"about_ca_system_score_gemma":0.001078509,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004732326,"about_ca_topic_score_gemma":0.0008839491,"domain_scores_codex":[0.9950609,0.003473046,0.00009100632,0.0002705776,0.0005393126,0.0005651662],"domain_scores_gemma":[0.9955333,0.002282014,0.0003318286,0.0006000147,0.0001652095,0.001087585],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00120281,0.005531238,0.006956451,0.0005641354,0.00003978708,0.001794315,0.06437925,0.007668021,0.01462685,0.05582948,0.02679117,0.8146166],"study_design_scores_gemma":[0.001306778,0.01389874,0.04194321,0.002286454,0.0001266655,0.008012684,0.09218308,0.04838587,0.03306438,0.1270431,0.6312682,0.0004809023],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5878314,0.0008947787,0.1721325,0.006892897,0.0007282464,0.0007338721,0.000120013,0.001726724,0.2289396],"genre_scores_gemma":[0.9319928,0.0004259876,0.04351953,0.000393501,0.00006537786,0.0003093265,0.00008430168,0.0001733917,0.02303577],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01513615,"threshold_uncertainty_score":0.05063546,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.221589991458692,"score_gpt":0.3703940178117552,"score_spread":0.1488040263530632,"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."}}