{"id":"W3048338996","doi":"10.18260/2-1-370.660-116661","title":"Computational Notebooks in Chemical Engineering Curricula","year":2020,"lang":"en","type":"article","venue":"Chemical Engineering Education","topic":"Experimental Learning in Engineering","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Variety (cybernetics); Curriculum; Computer science; Mathematics education; Computational thinking; Computer programming; Graduate students; Software engineering; Programming language; Multimedia; Artificial intelligence; Pedagogy; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00005405408,0.0003078925,0.0002559147,0.0001332355,0.00001151778,0.00003869656,0.000227345,0.0001584002,0.00003314157],"category_scores_gemma":[0.0001811119,0.0003928081,0.0000755983,0.0004020723,0.00001656983,0.0001567721,0.00004902565,0.0005612674,0.0000632014],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003186619,"about_ca_system_score_gemma":0.00003700994,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002929348,"about_ca_topic_score_gemma":1.551336e-8,"domain_scores_codex":[0.9987276,0.000004491909,0.0003644769,0.0003058539,0.0002156919,0.0003819123],"domain_scores_gemma":[0.9994645,0.00008111619,0.00001586362,0.0001494464,0.00002939808,0.0002597016],"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":[0.000001846466,0.00002258075,0.0000663901,0.000166917,0.000009100743,0.000002016001,0.0002742116,0.6153693,0.3828707,0.0003363672,0.0002277627,0.0006528183],"study_design_scores_gemma":[0.0002307726,0.000007113908,0.0001687596,0.0001319712,0.000006016978,0.00001209512,0.00001892481,0.8189876,0.1783565,0.00001239529,0.001682171,0.0003856684],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9615358,0.0006921632,0.03417111,0.0002018399,0.0007731909,0.0002631765,0.000004928362,0.001659008,0.0006988114],"genre_scores_gemma":[0.964835,0.000003340557,0.034394,0.00008225479,0.0004078937,0.00008903374,0.00007468275,0.0001087636,0.000004970309],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2045142,"threshold_uncertainty_score":0.9998524,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005189192505118102,"score_gpt":0.2090703936738441,"score_spread":0.203881201168726,"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."}}