{"id":"W7048828423","doi":"","title":"Natural Interaction for Serious Games : Enhancing Training Simulators through Automatic Speech Recognition","year":2010,"lang":"en","type":"article","venue":"NPARC","topic":"Lightning and Electromagnetic Phenomena","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Training (meteorology); Natural (archaeology); Natural language; Feature (linguistics); Action (physics)","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":[0.0007586628,0.0005959334,0.0003502681,0.0003611236,0.0002641739,0.0007568622,0.0007136107,0.0008164969,0.02366893],"category_scores_gemma":[0.006049351,0.000197002,0.0002129661,0.0001104484,0.0002141606,0.0007709254,0.0007292507,0.000424536,0.00749394],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000110295,"about_ca_system_score_gemma":0.0004002471,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006470574,"about_ca_topic_score_gemma":0.001608331,"domain_scores_codex":[0.9994887,0.0001903123,0.00002766328,0.00007753041,0.0001652946,0.00005051644],"domain_scores_gemma":[0.9978874,0.001100188,0.00009879004,0.0001276587,0.0005629085,0.0002231016],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002602616,0.002288272,0.01020044,0.0007401302,0.00007173331,0.0005337647,0.0009086739,0.003832064,0.2167618,0.0009258561,0.02060155,0.7405331],"study_design_scores_gemma":[0.001117278,0.01528243,0.1630348,0.0004577129,0.0005418514,0.003209413,0.002839026,0.340648,0.3365719,0.006743392,0.1292229,0.0003312805],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6602034,0.000595023,0.2532181,0.001270438,0.00102725,0.001386642,0.001005188,0.01044147,0.07085244],"genre_scores_gemma":[0.8907145,0.0003471817,0.0747094,0.0003327298,0.0001558591,0.0003789626,0.0007142271,0.0003603119,0.03228676],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02366893,"threshold_uncertainty_score":0.07918048,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01369719341350785,"score_gpt":0.263252885143208,"score_spread":0.2495556917297002,"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."}}