{"id":"W6930036534","doi":"10.5281/zenodo.10064740","title":"NanoSim pre-trained model: Human giab - AshkenaziTrio - Son - NA24385 - HG002 - Kit V14 - R10 - basecalled by dorado","year":2023,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"MicroRNA in disease regulation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Canada's Michael Smith Genome Sciences Centre","funders":"","keywords":"Python (programming language); Human genome; Sequence (biology); Software; Whole genome sequencing","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008368068,0.003978141,0.001438944,0.001290696,0.0009245503,0.001512621,0.004020274,0.002781641,0.04349722],"category_scores_gemma":[0.002534332,0.0009267614,0.002210616,0.001475834,0.0005175691,0.001009784,0.001649562,0.002620423,0.114737],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001650319,"about_ca_system_score_gemma":0.002242581,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0195705,"about_ca_topic_score_gemma":0.04456867,"domain_scores_codex":[0.9994013,0.00007380797,0.00002962852,0.000283554,0.0001198659,0.00009175009],"domain_scores_gemma":[0.9994324,0.0001255484,0.00002784299,0.0001965048,0.0001545322,0.00006313176],"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":[0.0002391345,0.00008192693,0.001760158,0.0004830993,0.00009222191,0.00006686929,0.00002436477,0.003173202,0.001532452,0.0004637152,0.9811292,0.01095374],"study_design_scores_gemma":[0.0008524774,0.0002662397,0.01046682,0.0004535747,0.0002796612,0.00080499,0.0001558578,0.03571462,0.01658306,0.006320516,0.9279436,0.0001586331],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.004246157,0.0007037533,0.005621021,0.0004074798,0.0003296428,0.0001142256,0.9579378,0.0257836,0.004856282],"genre_scores_gemma":[0.002328349,0.0001060361,0.003587513,0.0002072117,0.0000145679,0.0001798972,0.9897158,0.0009483901,0.002912346],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.04349722,"threshold_uncertainty_score":0.1455128,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01995217906688761,"score_gpt":0.2619976923022416,"score_spread":0.2420455132353539,"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."}}