{"id":"W4382343955","doi":"10.1186/s13059-023-02985-y","title":"ExplaiNN: interpretable and transparent neural networks for genomics","year":2023,"lang":"en","type":"article","venue":"Genome biology","topic":"Gene expression and cancer classification","field":"Biochemistry, Genetics and Molecular Biology","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Children's Hospital; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Genome Biology; Biology; Human genetics; Genomics; Computational genomics; Artificial neural network; Computational biology; Evolutionary biology; Personal genomics; Artificial intelligence; Genetics; Genome; Computer science; Gene","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001146436,0.00009783675,0.000107566,0.00004553198,0.00007424898,0.00001136238,0.0001158275,0.0001358501,0.0000105151],"category_scores_gemma":[0.0000124523,0.0000899234,0.00004719347,0.00006851953,0.00005361362,0.000001548201,0.00005809027,0.00003953664,0.000003655205],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009139651,"about_ca_system_score_gemma":0.0000176811,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000212225,"about_ca_topic_score_gemma":0.000006247023,"domain_scores_codex":[0.9992689,0.00003224703,0.0001360786,0.0003103849,0.00001862101,0.0002337668],"domain_scores_gemma":[0.9996825,0.00001117855,0.00004117799,0.0001799436,0.00002647258,0.00005869015],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001165585,0.000008893699,0.001060792,0.00001121128,0.00002567749,2.494129e-7,0.00007071955,0.001228164,0.9841321,0.0001796201,0.001428733,0.0117373],"study_design_scores_gemma":[0.001411159,0.0008327928,0.01568707,0.000005984305,0.00003115935,0.00001419202,0.0003179218,0.03021245,0.02954187,0.0005762943,0.920886,0.0004830801],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.91582,0.002450322,0.07994971,0.0005626291,0.0005612864,0.0003618489,0.00006639845,0.00004188811,0.0001859277],"genre_scores_gemma":[0.9970413,0.0009246189,0.0002014846,0.0003281426,0.0002762141,0.0001398645,0.0006552763,0.00001604239,0.0004170789],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9545902,"threshold_uncertainty_score":0.366697,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02998114762999924,"score_gpt":0.2846556744219202,"score_spread":0.254674526791921,"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."}}