{"id":"W4297474865","doi":"10.1093/nar/gkac832","title":"ProPan: a comprehensive database for profiling prokaryotic pan-genome dynamics","year":2022,"lang":"en","type":"article","venue":"Nucleic Acids Research","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"China Postdoctoral Science Foundation; National Natural Science Foundation of China","keywords":"Biology; Genome; Comparative genomics; Genomics; Computational biology; Adaptation (eye); Gene; Genetics","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":[0.00186916,0.00280641,0.003040527,0.01142647,0.001373916,0.002735029,0.002841372,0.001549417,0.007822207],"category_scores_gemma":[0.004474036,0.001325359,0.00174873,0.01591285,0.0004209049,0.003569127,0.004538964,0.001938128,0.007459842],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008006102,"about_ca_system_score_gemma":0.002757404,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002434226,"about_ca_topic_score_gemma":0.002959693,"domain_scores_codex":[0.9982018,0.0002531543,0.0003487184,0.0005797624,0.0004329771,0.000183439],"domain_scores_gemma":[0.9983996,0.0003316057,0.0003405547,0.0003750636,0.0002790585,0.0002741479],"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":[0.005536149,0.0007076205,0.03913745,0.04021299,0.002081115,0.003139748,0.002419357,0.008415913,0.1478427,0.01595628,0.45841,0.2761406],"study_design_scores_gemma":[0.0004549743,0.0002882433,0.03692018,0.00133104,0.0008084722,0.001531201,0.0007163162,0.01082326,0.02710849,0.01082741,0.9087901,0.0004002624],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.02427287,0.007892266,0.03921232,0.000213486,0.0001874323,0.0003429125,0.8793007,0.0424606,0.006117448],"genre_scores_gemma":[0.01584389,0.002507396,0.04649961,0.0001077549,0.00003089593,0.000535117,0.9321556,0.001690179,0.0006295572],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01142647,"threshold_uncertainty_score":0.02616793,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05895637072249147,"score_gpt":0.3358358159961474,"score_spread":0.2768794452736559,"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."}}