{"id":"W2607678022","doi":"10.18260/1-2--2720","title":"Student Curriculum Mapping: A More Authentic Way Of Examining And Evaluating Curriculum","year":2020,"lang":"en","type":"article","venue":"","topic":"Engineering Education and Curriculum Development","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Curriculum; Curriculum mapping; Process (computing); Emergent curriculum; Curriculum theory; Computer science; Perspective (graphical); Mathematics education; Curriculum development; Pedagogy; Psychology; Artificial intelligence","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":[],"consensus_categories":[],"category_scores_codex":[0.0001619041,0.000185911,0.0002268978,0.00007938722,0.00003536315,0.00003112793,0.0001389414,0.00004791081,0.0001713251],"category_scores_gemma":[0.00006904098,0.0001704773,0.00003385536,0.0003416059,0.0000211751,0.00007874044,0.00006652622,0.0001369574,0.00001935178],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004037219,"about_ca_system_score_gemma":0.00001785549,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000890648,"about_ca_topic_score_gemma":7.844689e-7,"domain_scores_codex":[0.9989111,0.0000153105,0.0003562549,0.0002109413,0.0002823941,0.0002240413],"domain_scores_gemma":[0.9995703,0.00002377127,0.00004317102,0.0001232463,0.0000653603,0.0001741241],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000005210432,0.0008608219,0.5149168,0.005013252,0.001111156,0.00003407855,0.1749589,0.1468818,0.05848571,0.005922205,0.03319804,0.05861206],"study_design_scores_gemma":[0.0008374673,0.0001347776,0.1696694,0.0002652976,0.00006262254,0.00001563808,0.02793478,0.7949486,0.002020954,0.00002087222,0.003356539,0.0007329829],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9912897,0.0004007661,0.005214311,0.0003108678,0.0003598097,0.0001972388,0.000001324117,0.0003502604,0.001875751],"genre_scores_gemma":[0.9911002,0.0000265626,0.008543044,0.00008299895,0.00006562993,0.0000361535,0.000006118461,0.00002784732,0.0001114824],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6480668,"threshold_uncertainty_score":0.6951861,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02902599226754797,"score_gpt":0.2790858741220099,"score_spread":0.2500598818544619,"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."}}