{"id":"W4391566281","doi":"10.1007/978-3-031-53022-7_31","title":"Adapting Experiential E-learning in Engineering Education with the Use of Telepresence System for Wind Tunnel Experiences in Automotive Engineering","year":2024,"lang":"en","type":"book-chapter","venue":"Lecture notes in networks and systems","topic":"Experimental Learning in Engineering","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Mohawk College; McMaster University","funders":"","keywords":"Experiential learning; Engineering; Automotive industry; Wind tunnel; Systems engineering; Aeronautics; Psychology; Aerospace engineering; Pedagogy","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002938104,0.0005246325,0.0006644087,0.0004694625,0.00003879831,0.0001577647,0.0001899834,0.0004023723,0.000001899239],"category_scores_gemma":[0.00008190246,0.0004399477,0.00007196893,0.0002523433,0.0000448586,0.0001682139,0.00006302086,0.001114531,3.601338e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003419399,"about_ca_system_score_gemma":0.0000346876,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001175581,"about_ca_topic_score_gemma":0.00007192643,"domain_scores_codex":[0.9982055,0.00002305911,0.0006364224,0.0004604431,0.0002272242,0.0004472959],"domain_scores_gemma":[0.9987924,0.0007547981,0.0001181399,0.0002319053,0.0000455971,0.00005717922],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000158738,0.000004796683,0.0001716875,0.001634933,0.00004628583,0.00001708441,0.007589526,0.9887048,0.0003867309,0.0008859049,0.000005029938,0.0005373667],"study_design_scores_gemma":[0.000192659,0.00005878621,0.00005078021,0.0100677,0.00001745128,0.00003682952,0.001451195,0.9856664,0.0001248985,0.000002414845,0.001883769,0.0004471395],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3369218,0.1175557,0.5256895,0.00004711091,0.009898609,0.006216133,0.00002516923,0.001474417,0.002171528],"genre_scores_gemma":[0.9977819,0.00008177376,0.0008706715,0.000002419173,0.000417793,0.0003737803,0.000015245,0.0001852772,0.0002711415],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6608601,"threshold_uncertainty_score":0.9998052,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01085373450815101,"score_gpt":0.2014491941367825,"score_spread":0.1905954596286314,"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."}}