{"id":"W3159082804","doi":"10.1016/j.ymeth.2021.05.001","title":"Deep networks and network representation in bioinformatics","year":2021,"lang":"en","type":"editorial","venue":"Methods","topic":"Gene expression and cancer classification","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Representation (politics); Computational biology; Computer science; Bioinformatics; Biology; Political science","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":[],"consensus_categories":[],"category_scores_codex":[0.0007737349,0.0001702598,0.0002468883,0.00005099529,0.00004680825,0.00005643948,0.0001317408,0.0007896258,0.00001423974],"category_scores_gemma":[0.0006031035,0.0001709429,0.00005941834,0.0002065729,0.00003689377,0.000003369593,0.0001589883,0.0003084846,7.275797e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002062014,"about_ca_system_score_gemma":0.0001125142,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001063343,"about_ca_topic_score_gemma":0.00004005111,"domain_scores_codex":[0.9985086,0.0004382132,0.0003307979,0.0003662731,0.0001529079,0.0002031648],"domain_scores_gemma":[0.9991117,0.0001240887,0.0001844812,0.000417652,0.0001030636,0.00005898313],"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":[0.0000331905,0.0000109037,0.0001186596,0.00003776261,0.00002288451,0.000001247492,0.00003749773,0.00370155,0.00195601,0.00000771638,0.9238656,0.07020696],"study_design_scores_gemma":[0.0003202501,0.0000368297,0.0001819955,0.00005753367,0.00002074837,0.000001210881,0.00008685289,0.01131164,0.001527627,0.00007479853,0.9861733,0.0002072435],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"editorial","genre_scores_codex":[0.00006417595,0.009425138,0.5809102,0.00004044339,0.4081672,0.0001654883,0.000003674201,0.000009814853,0.001213847],"genre_scores_gemma":[0.0001342657,0.01096743,0.2402268,0.0001472058,0.74431,0.0001066465,0.002356716,0.00005196872,0.001699041],"genre_candidate":"editorial","genre_consensus":null,"teacher_disagreement_score":0.3406834,"threshold_uncertainty_score":0.6970849,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01694355909140548,"score_gpt":0.3710437931840328,"score_spread":0.3541002340926273,"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."}}