{"id":"W4403765063","doi":"10.24908/pceea.2023.17133","title":"Guide to Backward Laboratory (Re)Design","year":2024,"lang":"en","type":"article","venue":"Proceedings of the Canadian Engineering Education Association (CEEA)","topic":"Biomedical and Engineering Education","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007560457,0.002148054,0.001213715,0.00368189,0.001323338,0.003483602,0.003940552,0.002154941,0.2163246],"category_scores_gemma":[0.02646078,0.00148063,0.001359199,0.002720424,0.001160525,0.002892032,0.002748996,0.003272673,0.1324107],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001736335,"about_ca_system_score_gemma":0.007283614,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005147302,"about_ca_topic_score_gemma":0.01219811,"domain_scores_codex":[0.9952706,0.001716875,0.0004969153,0.0004081515,0.00188944,0.0002181001],"domain_scores_gemma":[0.9806837,0.009203782,0.0005353444,0.002141345,0.006947012,0.0004887129],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001323218,0.0002290307,0.0005376562,0.001945495,0.00001959982,0.0004193018,0.00183212,0.002552129,0.004199114,0.03386196,0.4933184,0.4609529],"study_design_scores_gemma":[0.00003239078,0.0000398792,0.0002193724,0.0005710441,0.00000630155,0.0002252532,0.0002609421,0.001341252,0.001000221,0.00987401,0.9864036,0.000025707],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002284311,0.003416376,0.7152631,0.004092333,0.001299841,0.005514493,0.01527908,0.0365295,0.216321],"genre_scores_gemma":[0.006303753,0.002726129,0.8501141,0.00133718,0.0001303891,0.006243058,0.005929044,0.005326517,0.1218898],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2163246,"threshold_uncertainty_score":0.7236778,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004740830166205212,"score_gpt":0.2013818018637889,"score_spread":0.1966409716975837,"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."}}