{"id":"W2765816541","doi":"10.1177/1541931213601858","title":"Assessing the Training Effectiveness of an Intelligent Tutoring System for Marksmanship Skills","year":2017,"lang":"en","type":"article","venue":"Proceedings of the Human Factors and Ergonomics Society Annual Meeting","topic":"Intelligent Tutoring Systems and Adaptive Learning","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Computer science; Training (meteorology); Rifle; Training system; Task (project management); Control (management); Human–computer interaction; Virtual training; Artificial intelligence; Dreyfus model of skill acquisition; Simulation; Virtual reality; Multimedia; Applied psychology; Psychology; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001352069,0.0004255445,0.0003313051,0.0003227724,0.0001764338,0.0003315718,0.0004722657,0.0004902504,0.001773595],"category_scores_gemma":[0.01084721,0.0001263303,0.0001536084,0.0001297901,0.0002103443,0.0004180082,0.0003822403,0.0002955804,0.0002728168],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003191656,"about_ca_system_score_gemma":0.0004024866,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001736324,"about_ca_topic_score_gemma":0.001556163,"domain_scores_codex":[0.9992399,0.0002184271,0.00009533484,0.0001414766,0.000211179,0.00009374678],"domain_scores_gemma":[0.9958073,0.002409736,0.0004085802,0.0002714008,0.0005868724,0.0005161195],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.02262106,0.01914842,0.1647038,0.001007107,0.0003509096,0.0001733876,0.002624063,0.0203693,0.2268429,0.0003327993,0.001280615,0.5405456],"study_design_scores_gemma":[0.00140401,0.1233909,0.6351554,0.000099037,0.0008248744,0.0002857598,0.0009452867,0.07525186,0.1590926,0.0002548398,0.00319044,0.0001050328],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9975484,0.00003218128,0.00155914,0.00001104004,0.00001010257,0.0001104459,0.00002561808,0.00005896338,0.000644049],"genre_scores_gemma":[0.9964287,0.00002875856,0.002876335,0.000008567068,0.000006207174,0.00008359946,0.00006816645,0.000005153433,0.0004946205],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001773595,"threshold_uncertainty_score":0.007150531,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04149662542563953,"score_gpt":0.2958729657886649,"score_spread":0.2543763403630254,"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."}}