{"id":"W3206175213","doi":"10.1002/bmb.21584","title":"Enhancing science literacy and communication among the next generation of scientists in an online learning environment","year":2021,"lang":"en","type":"article","venue":"Biochemistry and Molecular Biology Education","topic":"Innovative Teaching Methods","field":"Social Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Scientific literacy; Coronavirus disease 2019 (COVID-19); Mathematics education; Active learning (machine learning); Literacy; Reflection (computer programming); Critical thinking; Science communication; Information literacy; Psychology; Computer science; Pedagogy; Science education; Medicine; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001548176,0.00004367298,0.00005277303,0.00003860116,0.0003830751,0.00005636384,0.0001051788,0.0000541095,0.000005282016],"category_scores_gemma":[0.0006146731,0.0000407732,0.000006810813,0.0002292924,0.0009380698,0.0001343489,0.00006255542,0.0001135883,7.32262e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005233295,"about_ca_system_score_gemma":0.0002878695,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002109092,"about_ca_topic_score_gemma":0.00005843262,"domain_scores_codex":[0.9990315,0.0004942394,0.0001223187,0.0001899858,0.00007005065,0.00009192439],"domain_scores_gemma":[0.9995882,0.00004763209,0.00009046626,0.0001533948,0.00009221896,0.00002811538],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[7.836556e-7,0.00004760359,0.02282077,0.000005191491,0.000001095633,8.951731e-8,0.004998307,0.000002338176,0.9548106,0.003398802,5.191573e-7,0.01391395],"study_design_scores_gemma":[0.00005939828,0.00001426702,0.04230466,0.00003195054,0.000004924981,0.000001979721,0.004621121,0.0002166694,0.9515386,0.0007274416,0.0004103126,0.00006867493],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9964042,0.000952527,0.001789813,0.0005184204,0.00005206512,0.00006059535,6.676817e-7,0.000003847658,0.0002178681],"genre_scores_gemma":[0.9856385,0.0001355232,0.01397401,0.00007112357,0.00003541317,0.000006764447,0.00006875207,0.000002035276,0.00006787033],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01948389,"threshold_uncertainty_score":0.3456357,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04608206935745846,"score_gpt":0.3998772798495764,"score_spread":0.353795210492118,"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."}}