{"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":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.003504772,0.0002241972,0.0003943391,0.00002849758,0.002296665,0.0008306285,0.001470644,0.0001005287,1.331858e-7],"category_scores_gemma":[0.0002819998,0.0001436904,0.0003031275,0.00005699327,0.0001874952,0.001234255,0.0005407431,0.0002454433,7.296115e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001120736,"about_ca_system_score_gemma":0.00003723092,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000149098,"about_ca_topic_score_gemma":0.000001648503,"domain_scores_codex":[0.9985954,0.00004519457,0.0004511187,0.0003835155,0.0001945554,0.0003301916],"domain_scores_gemma":[0.9978033,0.0004490843,0.001068387,0.0002940081,0.0003247837,0.00006039513],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0000470597,0.0001310123,0.1989437,0.004893524,0.0004499584,2.80926e-7,0.1456273,0.001239884,0.08989342,0.5511368,0.00001900704,0.00761801],"study_design_scores_gemma":[0.0008778187,0.000383613,0.4507073,0.007889884,0.0001524152,0.0000156202,0.1591636,0.01894013,0.3574252,0.00261248,0.0008679839,0.0009639336],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9946016,0.00004689986,0.003959827,0.00001836641,0.0005738592,0.0003782478,0.000005275913,0.00004226506,0.0003736461],"genre_scores_gemma":[0.9967088,0.000004197821,0.002976329,0.000004583997,0.0001930254,0.00001733362,5.28356e-7,0.00002197392,0.00007327112],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5485243,"threshold_uncertainty_score":0.9990022,"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."}}