{"id":"W1876341021","doi":"10.24908/pceea.v0i0.4688","title":"Do Engineering – Anywhere, Anytime","year":2012,"lang":"en","type":"article","venue":"Proceedings of the Canadian Engineering Education Association (CEEA)","topic":"Experimental Learning in Engineering","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Leverage (statistics); Scalability; Instrumentation (computer programming); Computer science; Engineering management; Space (punctuation); Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004409192,0.000287657,0.0002364509,0.0003945605,0.0001104533,0.0001112294,0.000388803,0.000232708,0.00007330327],"category_scores_gemma":[0.0005435194,0.0003138429,0.0001239339,0.0007061627,0.00001168471,0.0005440828,0.00003681627,0.0004481156,0.00004920612],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00321329,"about_ca_system_score_gemma":0.000134127,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007144269,"about_ca_topic_score_gemma":0.000110645,"domain_scores_codex":[0.9983653,0.000003981832,0.0003563984,0.0001683923,0.0003832655,0.0007226752],"domain_scores_gemma":[0.9990281,0.00005201168,0.0001349551,0.0001659762,0.0002020339,0.0004168971],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000003937877,0.0002007248,0.3482423,0.001683388,0.0007123824,3.289264e-7,0.006556376,0.3054449,0.2095543,0.03279728,0.0924826,0.00232149],"study_design_scores_gemma":[0.0006270574,0.00003588504,0.3685091,0.0008464386,0.000177541,0.00004158071,0.0007386006,0.08529591,0.08845031,0.00005901756,0.4531257,0.002092828],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9615583,0.002541691,0.000152298,0.0005209559,0.008808354,0.0006675523,0.0000343707,0.00113729,0.02457919],"genre_scores_gemma":[0.9949847,0.00001795296,0.003339591,0.00005029443,0.0005286601,0.00007608504,0.000006814742,0.0001248315,0.0008710814],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3606431,"threshold_uncertainty_score":0.9999314,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003777567382770231,"score_gpt":0.1855915600427595,"score_spread":0.1818139926599893,"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."}}