{"id":"W1893849089","doi":"10.24908/pceea.v0i0.5838","title":"CAPSTONE PROJECTS WITH LIMITED BUDGET AS AN EFFECTIVE METHOD FOR EXPERIENTIAL LEARNING","year":2015,"lang":"en","type":"article","venue":"Proceedings of the Canadian Engineering Education Association (CEEA)","topic":"Biomedical and Engineering Education","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Experiential learning; Capstone; Capstone course; Perspective (graphical); Engineering management; Work (physics); Computer science; Knowledge management; Engineering; Artificial intelligence; Mathematics education; Psychology; Mechanical engineering","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":[],"consensus_categories":[],"category_scores_codex":[0.0005265917,0.0001941956,0.0001928747,0.0003004134,0.0001095199,0.00009030164,0.0002097674,0.0001940827,0.000006766199],"category_scores_gemma":[0.001008922,0.0001767326,0.00005564697,0.0005981031,0.00001546834,0.0002930998,0.00001086908,0.0002693971,0.000004554921],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001835993,"about_ca_system_score_gemma":0.0004790244,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003458394,"about_ca_topic_score_gemma":0.001191953,"domain_scores_codex":[0.9989059,0.000009538669,0.0002110604,0.0002077009,0.0003086408,0.0003571716],"domain_scores_gemma":[0.9986622,0.00005995005,0.000121028,0.00009252415,0.000654418,0.0004098979],"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":[0.0002508296,0.001175504,0.05210381,0.00902017,0.002446591,0.000001238565,0.137928,0.3474451,0.09693202,0.03571435,0.2546312,0.0623512],"study_design_scores_gemma":[0.003406272,0.001070282,0.06956011,0.00103551,0.0005145554,0.00006688783,0.01134952,0.5258682,0.08671595,0.0009145454,0.2969385,0.002559566],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9843699,0.0001691857,0.004477799,0.001663203,0.004057179,0.001631098,0.00002455159,0.0006326023,0.002974477],"genre_scores_gemma":[0.9865521,0.000003134945,0.01143326,0.0000747831,0.0004143099,0.0005153736,0.00004381517,0.00007630291,0.0008869417],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1784231,"threshold_uncertainty_score":0.7206945,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006615026924238595,"score_gpt":0.2304984520203019,"score_spread":0.2238834250960633,"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."}}