{"id":"W4248994070","doi":"10.1515/iupac.88.1086","title":"Mycoplasma","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Microbial infections and disease research","field":"Immunology and Microbiology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Glossary; Terminology; Relation (database); Computer science; Linguistics; Philosophy; Data mining","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":[0.002150972,0.001587454,0.001953164,0.00516515,0.001188333,0.004476158,0.002154821,0.00228963,0.1180097],"category_scores_gemma":[0.01606686,0.0007976248,0.001480434,0.00790985,0.0005336952,0.002930389,0.002579541,0.002174017,0.1198604],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00145853,"about_ca_system_score_gemma":0.004375638,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0093192,"about_ca_topic_score_gemma":0.01429516,"domain_scores_codex":[0.9961382,0.0006457563,0.001064461,0.0009514792,0.0008785996,0.0003214763],"domain_scores_gemma":[0.993252,0.002155906,0.001149505,0.001473617,0.001636454,0.0003325247],"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":[0.0002237315,0.00002475583,0.002655117,0.005351752,0.00006672972,0.00007587388,0.00007565083,0.0001850324,0.0004687058,0.001616748,0.9718468,0.01740918],"study_design_scores_gemma":[0.00009643423,0.00001219363,0.002577284,0.001366482,0.00003258666,0.00009836117,0.00006222914,0.00008707107,0.000229394,0.001343525,0.9940758,0.00001859892],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002027449,0.000683149,0.0002523882,0.0002129013,0.0001205889,0.00005452736,0.9947959,0.0004681273,0.003209776],"genre_scores_gemma":[0.0007574916,0.0007069395,0.001120527,0.0004183131,0.00004009636,0.0001977222,0.9947484,0.0001534858,0.001856996],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1180097,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02048314740384727,"score_gpt":0.4426290776063391,"score_spread":0.4221459302024918,"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."}}