{"id":"W4412870783","doi":"10.24908/pceea.2025.19656","title":"Reinventing Design Learning in Bioengineering with Authenticity and Project-Based Learning","year":2025,"lang":"en","type":"article","venue":"Proceedings of the Canadian Engineering Education Association (CEEA)","topic":"Biomedical and Engineering Education","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Engineering; Engineering ethics; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.05034055,0.001205602,0.000723749,0.002449417,0.003877525,0.01460697,0.003627867,0.003052688,0.006205649],"category_scores_gemma":[0.07944811,0.0008162853,0.0008726212,0.001291196,0.009527974,0.009625149,0.02556672,0.006162727,0.002480431],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003540257,"about_ca_system_score_gemma":0.0108025,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005975458,"about_ca_topic_score_gemma":0.001330376,"domain_scores_codex":[0.9374275,0.04286269,0.001924937,0.003289738,0.0119005,0.002594737],"domain_scores_gemma":[0.9193935,0.03564498,0.006295695,0.01414301,0.01046509,0.01405779],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0001908905,0.005338802,0.0116977,0.001309038,0.00005558251,0.0006033238,0.1193609,0.004724304,0.008909199,0.07965278,0.01894215,0.7492154],"study_design_scores_gemma":[0.000369053,0.005206036,0.01722445,0.002786283,0.00007290429,0.003978711,0.07365477,0.01703984,0.01864494,0.2660423,0.5945823,0.0003984794],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2969333,0.001357343,0.5832271,0.0172014,0.0008468925,0.002771828,0.00007330061,0.001507058,0.0960819],"genre_scores_gemma":[0.5741615,0.0008095008,0.4040941,0.001912278,0.0002080114,0.001840706,0.0001256688,0.0003323769,0.01651587],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.05034055,"threshold_uncertainty_score":0.2662295,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004911679427578664,"score_gpt":0.1854225919232746,"score_spread":0.180510912495696,"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."}}