{"id":"W4394038895","doi":"10.5281/zenodo.4001160","title":"Annotree - GTDB archaea R95 database","year":2020,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Image Processing and 3D Reconstruction","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Archaea; Database; Computer science; Biology; Genetics; Bacteria","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":[0.001139743,0.003058484,0.002009074,0.004898089,0.001288456,0.002161469,0.003603469,0.001930596,0.04909154],"category_scores_gemma":[0.003036017,0.001006587,0.001830789,0.006958146,0.0005068337,0.001332888,0.002097558,0.001725389,0.08583772],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001139484,"about_ca_system_score_gemma":0.002653429,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01572492,"about_ca_topic_score_gemma":0.02226799,"domain_scores_codex":[0.9987611,0.0001696013,0.000171798,0.0004247214,0.0002633237,0.0002094792],"domain_scores_gemma":[0.9986512,0.0002770186,0.0001261352,0.0004805595,0.0002893697,0.0001756373],"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":[0.0003902956,0.00007945686,0.001377804,0.001951606,0.00008723509,0.00008393326,0.00007313064,0.0009053565,0.001830894,0.0009125021,0.9867213,0.005586539],"study_design_scores_gemma":[0.0003339279,0.00005432503,0.004159977,0.0002852252,0.00008949964,0.0001552852,0.0001560695,0.001146843,0.002215972,0.001321638,0.9900154,0.00006588367],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0004466175,0.00006415787,0.000161424,0.00001997555,0.00001979941,0.00001434844,0.9976469,0.00106578,0.0005609502],"genre_scores_gemma":[0.000310343,0.00003042837,0.0003320404,0.00001418047,0.000001701826,0.00004308754,0.9989086,0.000127162,0.0002325025],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.04909154,"threshold_uncertainty_score":0.1642276,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03536175358566442,"score_gpt":0.2451956677852548,"score_spread":0.2098339141995904,"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."}}