{"id":"W1787061638","doi":"10.1023/a:1012045305968","title":"Using VR for Efficient Training of Forestry Machine Operators","year":2000,"lang":"en","type":"article","venue":"Education and Information Technologies","topic":"Forest Biomass Utilization and Management","field":"Engineering","cited_by":40,"is_retracted":false,"has_abstract":false,"ca_institutions":"Polytechnique Montréal; National Research Council Canada","funders":"","keywords":"Computer science; Training (meteorology); Virtual reality; Field (mathematics); Multimedia; Simulation; Human–computer interaction; Artificial intelligence; Mathematics","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":[0.0002674624,0.0002154727,0.0001385695,0.0002273822,0.0001747805,0.0004550673,0.0003676454,0.0005053465,0.006233728],"category_scores_gemma":[0.001110827,0.0001334653,0.0001673916,0.0001960409,0.0001151204,0.0004403552,0.0002732969,0.0003606897,0.0005137665],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001393854,"about_ca_system_score_gemma":0.0003302884,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0024877,"about_ca_topic_score_gemma":0.004283038,"domain_scores_codex":[0.9998466,0.00005811848,0.000005919949,0.00002058539,0.00004651376,0.00002223618],"domain_scores_gemma":[0.9996393,0.000249373,0.00002089522,0.00003364876,0.00003996343,0.00001687158],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004191933,0.0005751331,0.003568369,0.0002673943,0.00003684746,0.0004329939,0.00104822,0.06998555,0.1711155,0.004664978,0.003671353,0.7442145],"study_design_scores_gemma":[0.0002627964,0.001732021,0.03223524,0.000289028,0.0001780351,0.001867489,0.001523192,0.7755529,0.1091422,0.01234738,0.06474505,0.000124672],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.4781477,0.0005892946,0.4803053,0.0005551957,0.0001386691,0.0001320614,0.0001804933,0.001336621,0.03861476],"genre_scores_gemma":[0.857315,0.0003820367,0.1351195,0.00008641517,0.00003314217,0.00007224749,0.0001072689,0.00006311895,0.006821373],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006233728,"threshold_uncertainty_score":0.02085388,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01449158580154249,"score_gpt":0.2420651481793215,"score_spread":0.227573562377779,"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."}}