{"id":"W4400090968","doi":"10.62492/sefijeea.v1i1.15","title":"A Causation-driven Approach to Engineering Education Using Data Analytics and Machine Learning Tools","year":2024,"lang":"en","type":"article","venue":"SEFI Journal of Engineering Education Advancement","topic":"Advanced Data Processing Techniques","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Causation; Analytics; Data science; Data analysis; Computer science; Learning analytics; Machine learning; Artificial intelligence; Data mining; Epistemology","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":[0.0003132046,0.0002350439,0.0002344945,0.0006172123,0.00004639208,0.0002088972,0.0002978042,0.00005402294,0.000006095214],"category_scores_gemma":[0.0002758794,0.0002509826,0.00003125563,0.0005164184,0.000009135938,0.001087168,0.0000964396,0.00039417,0.000002149437],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004317734,"about_ca_system_score_gemma":0.0002736484,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004074004,"about_ca_topic_score_gemma":4.951586e-7,"domain_scores_codex":[0.9987677,0.00001069234,0.000503418,0.0002478632,0.000246778,0.0002235078],"domain_scores_gemma":[0.9991967,0.0000691506,0.00008728897,0.0003291398,0.0001473505,0.0001703652],"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":[0.00000311216,0.00005224038,0.00004837902,0.0007604355,0.0000674208,0.000001259482,0.0002986405,0.9418054,0.01203169,0.0008816112,0.0003442361,0.0437056],"study_design_scores_gemma":[0.00007227901,0.00003481672,0.00009058865,0.0009489813,0.00005934296,0.0001354554,0.0001355562,0.8978555,0.0009942816,0.00004597818,0.09935381,0.0002733885],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01423505,0.009975033,0.9738213,0.00009354085,0.001304458,0.0002075655,0.00002600647,0.0002539404,0.00008305367],"genre_scores_gemma":[0.370493,0.001121136,0.6276039,0.00003222001,0.0004561534,0.0000197661,0.0001387787,0.00008931737,0.00004568846],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.356258,"threshold_uncertainty_score":0.9999942,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05136942660026241,"score_gpt":0.315144186839928,"score_spread":0.2637747602396656,"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."}}