{"id":"W3001250508","doi":"10.24908/pceea.vi0.13468","title":"A Decision-Making Framework for Engineering Mathematics Education","year":2019,"lang":"en","type":"article","venue":"Proceedings of the Canadian Engineering Education Association (CEEA)","topic":"Engineering Education and Curriculum Development","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Creativity; Theme (computing); Engineering mathematics; Mathematics education; Engineering education; Engineering ethics; Computer science; Management science; Mathematics; Engineering; Engineering management; Political science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.0003642265,0.0002670536,0.0002553081,0.0004613128,0.00009621032,0.0001443417,0.000420298,0.0002565294,0.00006978969],"category_scores_gemma":[0.001451247,0.0002801822,0.0001441166,0.0007123366,0.000005901637,0.0002404392,0.00002265282,0.0003040426,0.00003859162],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00272427,"about_ca_system_score_gemma":0.0008095637,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001146963,"about_ca_topic_score_gemma":0.0001620368,"domain_scores_codex":[0.9985152,0.000001878743,0.0004680737,0.0002258094,0.0003544297,0.000434557],"domain_scores_gemma":[0.9986224,0.0002206516,0.0002048128,0.000200652,0.0005472619,0.0002041777],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000007566342,0.0005501362,0.07201133,0.008453539,0.0007867493,9.371297e-8,0.008511379,0.1850913,0.007885509,0.5009016,0.1883526,0.02744816],"study_design_scores_gemma":[0.0008395,0.00006198334,0.1824973,0.008873135,0.0003050691,0.00003183211,0.002779252,0.2936413,0.007239469,0.0131301,0.4875244,0.003076683],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9262965,0.001005396,0.02073013,0.002377012,0.03558039,0.003952348,0.00007898701,0.001229531,0.008749709],"genre_scores_gemma":[0.897321,0.00001558097,0.1008569,0.0001577954,0.0002937012,0.0003207505,0.00001078477,0.0001072292,0.0009162622],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4877715,"threshold_uncertainty_score":0.999965,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00316187718220595,"score_gpt":0.2086319066678481,"score_spread":0.2054700294856422,"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."}}