{"id":"W6958790585","doi":"10.6084/m9.figshare.3507545","title":"An approximate maximum likelihood phylogenetic tree of sequenced streptomycetes (PDF)","year":2016,"lang":"en","type":"other","venue":"Figshare","topic":"Digital Transformation in Industry","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Phylogenetic tree; Tree (set theory); Phylogenetics; Computational phylogenetics; Sequence (biology); Maximum likelihood; Tree of life (biology)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001858637,0.001678815,0.001938229,0.004480474,0.002792294,0.004241507,0.002240117,0.003055813,0.0686405],"category_scores_gemma":[0.01063829,0.001065114,0.001921008,0.009402231,0.0006560736,0.002475757,0.001156445,0.003582484,0.04924003],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001809229,"about_ca_system_score_gemma":0.002173356,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003495617,"about_ca_topic_score_gemma":0.005554827,"domain_scores_codex":[0.9988152,0.000341062,0.00009355049,0.0003703016,0.0002558146,0.0001240963],"domain_scores_gemma":[0.9964899,0.001526355,0.0003548368,0.0003881871,0.0008866877,0.0003540639],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.006254121,0.0007445124,0.02685839,0.01523912,0.001195853,0.003980046,0.005584136,0.08499343,0.0677958,0.02063342,0.4355891,0.3311321],"study_design_scores_gemma":[0.000717284,0.00058005,0.04812438,0.003857734,0.0007414935,0.003986635,0.005042889,0.1423544,0.007024431,0.03392272,0.7531018,0.0005462198],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.08631624,0.007849758,0.200463,0.003222043,0.003040118,0.001668931,0.6200634,0.02646544,0.05091109],"genre_scores_gemma":[0.2162636,0.003944227,0.2924627,0.0008352919,0.000367686,0.001121275,0.4631,0.005429693,0.01647569],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0686405,"threshold_uncertainty_score":0.2296253,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01823418785890758,"score_gpt":0.2349660891871326,"score_spread":0.2167319013282251,"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."}}