{"id":"W6920769586","doi":"10.6084/m9.figshare.23590429.v1","title":"Additional file 2 of ExplaiNN: interpretable and transparent neural networks for genomics","year":2023,"lang":"en","type":"article","venue":"Figshare","topic":"Machine Learning in Bioinformatics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Children's Hospital","funders":"","keywords":"Artificial neural network; Genomics; Feature (linguistics); File format; Pattern recognition (psychology)","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00001581413,0.0000693583,0.00007380122,0.0000199046,0.00003662295,0.00001077846,0.00008699978,0.00006851734,0.6269666],"category_scores_gemma":[0.0006141409,0.00006933572,0.00004672098,0.00004243766,0.000007299238,0.00000283885,0.00006442114,0.00004754683,0.00003587141],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003345554,"about_ca_system_score_gemma":0.00001863889,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":2.685722e-7,"about_ca_topic_score_gemma":0.000002722334,"domain_scores_codex":[0.9996103,0.000008112725,0.0001194517,0.0000983662,0.00004087413,0.0001229138],"domain_scores_gemma":[0.9996011,0.0001650379,0.00006331094,0.00009873558,0.00003967325,0.00003214416],"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":[0.00001314427,0.000003442896,0.000002292451,0.0000794882,0.00001168551,2.242941e-7,0.00002164164,0.003198261,0.00007194235,7.75716e-7,0.9947349,0.001862189],"study_design_scores_gemma":[0.0000910596,0.00007785466,0.0002864406,0.0001228993,0.000002119533,0.000003353165,0.00001706096,0.2127241,0.0001890795,0.000003522216,0.786414,0.00006856964],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001988491,0.00003412538,0.00006806081,0.00001398307,0.00001632254,0.0001175365,0.9990277,0.00001417681,0.0005092017],"genre_scores_gemma":[0.008999109,0.000003240926,0.000832915,0.00009209913,0.00009900233,0.0004074363,0.9890758,0.0000125086,0.0004778446],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.6269307,"threshold_uncertainty_score":0.3733744,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01977128704959072,"score_gpt":0.2491596745858259,"score_spread":0.2293883875362351,"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."}}