{"id":"W4233077764","doi":"10.1515/iupac.88.1369","title":"Stem Cell","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Pluripotent Stem Cells Research","field":"Biochemistry, Genetics and Molecular Biology","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; Data mining; Philosophy","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":[0.001969748,0.001025736,0.00141266,0.004280409,0.001056094,0.003973062,0.002124411,0.001709255,0.1446553],"category_scores_gemma":[0.01223907,0.0006924137,0.001416662,0.00788363,0.0004106966,0.001919205,0.002692287,0.001830125,0.1315188],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001174327,"about_ca_system_score_gemma":0.003808029,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007530541,"about_ca_topic_score_gemma":0.01670868,"domain_scores_codex":[0.9981716,0.0002880995,0.0004725863,0.0004313328,0.0004394317,0.0001969377],"domain_scores_gemma":[0.9953777,0.001578931,0.000483855,0.001133623,0.001092317,0.000333572],"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":[0.0001200869,0.00001432945,0.00147046,0.003127147,0.00006725612,0.00004515358,0.00005153087,0.0002006658,0.0003964473,0.002118987,0.9694928,0.02289519],"study_design_scores_gemma":[0.00007715367,0.00001219432,0.001709282,0.0008612135,0.00003269279,0.00006616412,0.00003989596,0.00007892127,0.0002676442,0.001656504,0.9951841,0.00001417766],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001547468,0.0005975386,0.0002915843,0.0001958482,0.0001055713,0.00003540667,0.995043,0.0003395898,0.003236728],"genre_scores_gemma":[0.0004591465,0.0005420709,0.000735352,0.0002651992,0.00002351084,0.0001520855,0.995953,0.00009407063,0.001775472],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1446553,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01703814402624794,"score_gpt":0.4028490740474181,"score_spread":0.3858109300211702,"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."}}