{"id":"W1886361645","doi":"10.1002/bmb.20823","title":"A guide to using case‐based learning in biochemistry education","year":2014,"lang":"en","type":"article","venue":"Biochemistry and Molecular Biology Education","topic":"Problem and Project Based Learning","field":"Social Sciences","cited_by":85,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Memorization; Rote learning; Active learning (machine learning); Class (philosophy); Process (computing); Psychology; Value (mathematics); Teaching method; Mathematics education; Chemistry; Biochemistry; Computer science; Cooperative learning; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006081164,0.002382641,0.001483312,0.006078476,0.001194231,0.002959066,0.004127513,0.00410823,0.06305986],"category_scores_gemma":[0.01645716,0.001969377,0.001188118,0.004078504,0.001367136,0.004270231,0.003393519,0.004978512,0.04440834],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001664201,"about_ca_system_score_gemma":0.004591854,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003182524,"about_ca_topic_score_gemma":0.01228466,"domain_scores_codex":[0.9962691,0.001654809,0.0006336256,0.0001973619,0.001089622,0.0001554765],"domain_scores_gemma":[0.983555,0.01197802,0.0007292445,0.0007878745,0.002208844,0.0007409623],"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":[0.0000616898,0.0006755601,0.0004493924,0.001785424,0.00002014546,0.001255218,0.001674175,0.001395656,0.001725724,0.01389701,0.5002211,0.476839],"study_design_scores_gemma":[0.00004778477,0.0001011838,0.0008025084,0.001808627,0.00000617241,0.002054149,0.0004979206,0.001081019,0.0003154899,0.01434876,0.9788861,0.00005032648],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004911773,0.02418364,0.6331231,0.03001614,0.00374687,0.02075491,0.01228169,0.02321558,0.2477663],"genre_scores_gemma":[0.004722181,0.0155226,0.8785577,0.006995559,0.0004302162,0.007978186,0.004585613,0.001361325,0.07984664],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.06305986,"threshold_uncertainty_score":0.2109563,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01010405474044868,"score_gpt":0.3602833571514276,"score_spread":0.3501793024109789,"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."}}