{"id":"W1966666479","doi":"10.1093/bib/bbt016","title":"Navigating the changing learning landscape: perspective from bioinformatics.ca","year":2013,"lang":"en","type":"article","venue":"Briefings in Bioinformatics","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Institute for Cancer Research","funders":"Canadian Institutes of Health Research; Genome Canada; Ontario Genomics; Amazon Web Services; Ontario Institute for Cancer Research; Ontario Genomics Institute","keywords":"Computer science; Perspective (graphical); Face (sociological concept); Structural bioinformatics; Bioinformatics; World Wide Web; Data science; Artificial intelligence; Biology; Sociology","routes":{"ca_aff":true,"ca_fund":true,"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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008030143,0.0003355269,0.0002978286,0.0001203924,0.0003846987,0.0003485962,0.000683444,0.0002998181,0.0001845153],"category_scores_gemma":[0.001166533,0.0002457536,0.0001471228,0.0004886565,0.0003278556,0.00006671983,0.0006112436,0.0009020062,0.0004671971],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007719206,"about_ca_system_score_gemma":0.0001414176,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009604548,"about_ca_topic_score_gemma":0.00007621261,"domain_scores_codex":[0.9972513,0.00006630328,0.0009141848,0.000239935,0.0006128158,0.0009154179],"domain_scores_gemma":[0.9984932,0.0001459265,0.0003372829,0.0005075081,0.0003071711,0.0002089076],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002675473,0.0005785669,0.03760452,0.001176428,0.0009102642,0.00002117371,0.1544696,0.002932899,0.01405695,0.001876975,0.09124716,0.6948579],"study_design_scores_gemma":[0.003326322,0.0008016416,0.007818162,0.0006952154,0.00005819316,0.00007664712,0.1828717,0.7211007,0.01296983,0.001915739,0.06666742,0.001698373],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9461644,0.001181139,0.01479302,0.007341192,0.0005027854,0.001828286,0.00008573395,0.0001280501,0.02797538],"genre_scores_gemma":[0.9534712,0.001287349,0.03744759,0.005521568,0.0006202881,0.0001579081,0.0006776212,0.0000708646,0.0007455976],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7181678,"threshold_uncertainty_score":0.9999995,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01006027325739789,"score_gpt":0.2676827681150437,"score_spread":0.2576224948576458,"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."}}