{"id":"W2602711680","doi":"10.24908/pceea.v0i0.6463","title":"BUILDING A MORE COMPLETE DESIGN EXPERIENCE: PHILOSOPHIES AND REFLECTIONS FROM A SECOND YEAR MECHANICAL ENGINEERING DESIGN PROJECT COURSE","year":2017,"lang":"en","type":"article","venue":"Proceedings of the Canadian Engineering Education Association (CEEA)","topic":"Engineering Education and Curriculum Development","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Teamwork; Engineering design process; Curriculum; Process (computing); Engineering management; Engineering; Project-based learning; Design process; Mathematics education; Computer science; Work in process; Psychology; Pedagogy; Mechanical engineering; Operations management","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003389211,0.0002596642,0.0002426454,0.0002688361,0.0003858733,0.0003329778,0.0004501264,0.0001855359,0.00002816018],"category_scores_gemma":[0.0007185335,0.0002747783,0.00006606401,0.0002730462,0.00002818329,0.0003753457,0.00004459072,0.0003232504,0.000004300865],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001187573,"about_ca_system_score_gemma":0.0004624226,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001119548,"about_ca_topic_score_gemma":0.0004201931,"domain_scores_codex":[0.9987472,0.000007007379,0.0003184548,0.0002613472,0.0002899863,0.0003760023],"domain_scores_gemma":[0.9990465,0.0000785662,0.0001990025,0.0002192365,0.0002589633,0.0001977032],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0000443145,0.0006004409,0.03295016,0.002795211,0.003147993,0.000003961394,0.05091846,0.1629819,0.4227518,0.09935877,0.2184167,0.006030323],"study_design_scores_gemma":[0.001842641,0.0001018864,0.4020631,0.002076108,0.0004689179,0.0000545509,0.003523372,0.3434231,0.07878111,0.002524186,0.1616135,0.003527488],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.928688,0.001598736,0.03140382,0.01203126,0.01613241,0.004429302,0.0002934743,0.001956747,0.003466196],"genre_scores_gemma":[0.9496179,0.00003222683,0.04950252,0.00005868678,0.0002215293,0.0002406075,0.0000056094,0.00006911778,0.000251775],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3691129,"threshold_uncertainty_score":0.9999704,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03425804111233875,"score_gpt":0.2740804380688481,"score_spread":0.2398223969565094,"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."}}