{"id":"W1999677527","doi":"10.1007/s10142-004-0129-7","title":"Looking through genomics?from the editors","year":2004,"lang":"en","type":"editorial","venue":"Functional & Integrative Genomics","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Department of Environment and Conservation","funders":"","keywords":"Biology; Genomics; Computational biology; Data science; Genome; Computer science; Genetics; Gene","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":[0.01194941,0.0044888,0.005371493,0.004228446,0.003621507,0.01069394,0.004335107,0.01470202,0.01089517],"category_scores_gemma":[0.02611603,0.001543653,0.002304444,0.001705798,0.003807493,0.007326384,0.002561281,0.02884077,0.007988184],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003023715,"about_ca_system_score_gemma":0.003292928,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002064903,"about_ca_topic_score_gemma":0.005736778,"domain_scores_codex":[0.9941518,0.001387334,0.0007365519,0.0007320916,0.002592013,0.0004002543],"domain_scores_gemma":[0.9727979,0.01007937,0.00137823,0.0007727605,0.0105144,0.004457296],"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":[0.0000342994,0.000008783531,0.00001729955,0.0001397901,0.00001560062,0.00007433901,0.00001803111,0.00002137391,0.00004425847,0.000424936,0.9946153,0.004586],"study_design_scores_gemma":[0.00004804921,0.00002250711,0.0001374729,0.0003965134,0.00004775237,0.0001863781,0.00006079459,0.00008179223,0.00007171658,0.001045025,0.9978786,0.0000234063],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.00002049634,0.01043732,0.0001050407,0.05343845,0.9349667,0.000009430596,0.00001839563,0.00002828678,0.0009758829],"genre_scores_gemma":[0.0003701829,0.007454599,0.0001196659,0.05135896,0.9308879,0.00002371534,0.00001960607,0.00003994675,0.009725504],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.01470202,"threshold_uncertainty_score":0.06319523,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01011729689997026,"score_gpt":0.2380408704929469,"score_spread":0.2279235735929766,"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."}}