{"id":"W6893614615","doi":"10.5281/zenodo.3993421","title":"PhyloCorrelate: prediction of gene-gene functional associations through large-scale phylogenetic profiling","year":2020,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Phylogenetic tree; Genome; Profiling (computer programming); Annotation; Row; Bacterial genome size","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":[0.0009875365,0.001548589,0.00118997,0.00210766,0.0006805981,0.001362758,0.0008719275,0.0005659725,0.01575397],"category_scores_gemma":[0.00177981,0.0006110959,0.001106731,0.002039267,0.0002986251,0.0008593819,0.001732754,0.0009633265,0.0113189],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003955914,"about_ca_system_score_gemma":0.0007203913,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001357441,"about_ca_topic_score_gemma":0.002687753,"domain_scores_codex":[0.9994678,0.0000804144,0.0000335899,0.0002466973,0.0001026641,0.00006875512],"domain_scores_gemma":[0.9994554,0.0001775491,0.00009382809,0.0001072975,0.0000502318,0.0001155738],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.007188998,0.0006695914,0.08297087,0.00542316,0.001382016,0.001874196,0.001202467,0.009350946,0.4160926,0.005879199,0.3490533,0.1189127],"study_design_scores_gemma":[0.001787834,0.00180762,0.2454247,0.0007846352,0.001065186,0.005720277,0.001205662,0.1634173,0.1381422,0.01561099,0.4244983,0.0005353047],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.1983182,0.00204025,0.08459266,0.0005056199,0.0002685614,0.0003034924,0.6232428,0.08192683,0.008801579],"genre_scores_gemma":[0.175284,0.0009609913,0.104571,0.0002141061,0.00005889138,0.0003793401,0.7078615,0.007645352,0.003024829],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01575397,"threshold_uncertainty_score":0.05270225,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02707909359460433,"score_gpt":0.2196605806874757,"score_spread":0.1925814870928714,"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."}}