{"id":"W4417046158","doi":"10.1093/bioadv/vbaf311","title":"Mapping educational needs in bioinformatics in Brazil: adapting ISCB 3.0 competencies to a regional context","year":2024,"lang":"en","type":"article","venue":"Bioinformatics Advances","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hospital for Sick Children","funders":"","keywords":"Context (archaeology); Curriculum; Socioeconomic status; Scalability; Curriculum framework","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":[0.0007818095,0.0003040678,0.0003095827,0.00101471,0.00009645884,0.0002049592,0.0005051717,0.0001944139,0.00003848981],"category_scores_gemma":[0.0004671138,0.0002700307,0.0001142126,0.001087665,0.0002240329,0.0001023708,0.0002931246,0.0002916783,0.0001929616],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001102268,"about_ca_system_score_gemma":0.0005252362,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004063512,"about_ca_topic_score_gemma":0.0004345158,"domain_scores_codex":[0.9972851,0.00003428359,0.001160607,0.0002239797,0.0005988003,0.0006972246],"domain_scores_gemma":[0.998997,0.000150551,0.0001276836,0.0003276754,0.0001379105,0.0002591201],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003349359,0.0005004848,0.01354743,0.005748697,0.0002154619,0.00002606455,0.04482907,0.003308308,0.01624182,0.009598131,0.04129029,0.8643593],"study_design_scores_gemma":[0.001156795,0.0005634983,0.004638145,0.001391224,0.000008773578,0.0000777119,0.03465816,0.1149484,0.00268201,0.001058024,0.83782,0.0009972579],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8621675,0.02289878,0.05088609,0.01717292,0.003012805,0.003261964,0.0003435487,0.0001953776,0.04006098],"genre_scores_gemma":[0.896901,0.004028619,0.09257966,0.003699613,0.000571261,0.0001557349,0.000552609,0.00005298817,0.001458488],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8633621,"threshold_uncertainty_score":0.9999752,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02452441183690168,"score_gpt":0.306922608021887,"score_spread":0.2823981961849854,"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."}}