{"id":"W4393649471","doi":"10.5281/zenodo.1034451","title":"Annotree: Visualization And Exploration Of Protein Domain Families Across The Tree Of Life","year":2017,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Tree of life (biology); Domain (mathematical analysis); Tree (set theory); Visualization; Family tree; Evolutionary biology; Forestry; Computer science; Geography; Biology; Phylogenetic tree; Genealogy; Mathematics; Data mining; Combinatorics; History; 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":[0.0006588243,0.002094408,0.001181851,0.004179855,0.0008571134,0.00213076,0.002105925,0.001191523,0.04338451],"category_scores_gemma":[0.002948935,0.00055822,0.001402798,0.004367965,0.0003285492,0.001520158,0.002075144,0.001876615,0.02940888],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001034856,"about_ca_system_score_gemma":0.001498748,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01010627,"about_ca_topic_score_gemma":0.02870418,"domain_scores_codex":[0.999459,0.00007644095,0.0000584819,0.0002053136,0.0001258996,0.00007478679],"domain_scores_gemma":[0.9988707,0.0003971253,0.0001134936,0.0002346962,0.000228299,0.0001557039],"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":[0.0001660393,0.00003905052,0.001973942,0.00142364,0.00006861283,0.0000753775,0.00009179222,0.0005946965,0.001027878,0.001373998,0.9867518,0.006413156],"study_design_scores_gemma":[0.0001964069,0.00002699159,0.005298411,0.0004522818,0.00006283992,0.0002721866,0.0001803818,0.002840753,0.001718592,0.003541894,0.9853635,0.00004568485],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001170858,0.0003427009,0.0007973519,0.000137394,0.00005052828,0.00001592297,0.9921626,0.003986716,0.001335842],"genre_scores_gemma":[0.001808619,0.0002277426,0.002035902,0.00005297819,0.000006640464,0.00004298741,0.9946892,0.0004005675,0.0007353171],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.04338451,"threshold_uncertainty_score":0.1451357,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03647679588647684,"score_gpt":0.3030591288791397,"score_spread":0.2665823329926628,"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."}}