{"id":"W2044240998","doi":"10.1371/journal.pone.0087126","title":"MetaMetaDB: A Database and Analytic System for Investigating Microbial Habitability","year":2014,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Core Research for Evolutional Science and Technology; Institute of Genetics; Japan Science and Technology Agency; Japan Society for the Promotion of Science; Research Organization of Information and Systems","keywords":"Metagenomics; Habitability; 16S ribosomal RNA; Ribosomal RNA; Biology; Computational biology; Prokaryote; Genetics; Bacteria; Gene","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006257917,0.002477661,0.002943358,0.009867661,0.001469505,0.004767449,0.005116996,0.001681286,0.01150999],"category_scores_gemma":[0.01217968,0.001555672,0.001950588,0.008970737,0.0006196682,0.006750218,0.005508736,0.002484301,0.008089161],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00106531,"about_ca_system_score_gemma":0.003308392,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003164783,"about_ca_topic_score_gemma":0.002459335,"domain_scores_codex":[0.9975877,0.000401321,0.0006172864,0.0006428998,0.0005315661,0.0002191872],"domain_scores_gemma":[0.9942412,0.002014682,0.000786329,0.001304556,0.0009635536,0.0006897078],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.005263638,0.001011376,0.03204591,0.01017024,0.001790365,0.001442119,0.001605595,0.007611748,0.05285027,0.02021641,0.5580153,0.3079771],"study_design_scores_gemma":[0.001311969,0.0006104553,0.02738697,0.001060917,0.0009970366,0.001473494,0.0009727487,0.07892845,0.06271296,0.03579392,0.7879568,0.0007943627],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"software","genre_scores_codex":[0.02068203,0.003069508,0.2174934,0.0008294733,0.0004758774,0.0011393,0.3836851,0.3637834,0.008842013],"genre_scores_gemma":[0.05283002,0.002360114,0.3098251,0.0009403289,0.0001707912,0.002969449,0.6148243,0.01320461,0.002875348],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.01150999,"threshold_uncertainty_score":0.03850472,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03813610369930368,"score_gpt":0.2231219492325265,"score_spread":0.1849858455332228,"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."}}