{"id":"W4256386271","doi":"10.1515/iupac.88.1241","title":"Primordial Germ Cell","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Xenotransplantation and immune response","field":"Medicine","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":[0.00118359,0.001115967,0.001281647,0.003792059,0.0007581684,0.002575703,0.001859572,0.001218121,0.07163935],"category_scores_gemma":[0.008441598,0.0005645744,0.001594349,0.005704817,0.0004394794,0.001607965,0.001770978,0.001735024,0.05348845],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001188327,"about_ca_system_score_gemma":0.00289212,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0123066,"about_ca_topic_score_gemma":0.02169626,"domain_scores_codex":[0.9988343,0.0001684515,0.0002754242,0.0003501536,0.0002388026,0.0001328471],"domain_scores_gemma":[0.9965171,0.001185595,0.0006161884,0.000820286,0.0006291217,0.0002317139],"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":[0.0002770422,0.00002118181,0.00572953,0.004915434,0.0001272819,0.00009834543,0.00006532315,0.000474872,0.0005283848,0.001785124,0.9639969,0.02198054],"study_design_scores_gemma":[0.0001403128,0.00002343773,0.009312101,0.001214186,0.00008193328,0.00022731,0.00006284559,0.0001675504,0.0004034944,0.001831195,0.9865094,0.00002630414],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003386445,0.0007412872,0.0002725252,0.000110468,0.00007312399,0.00003158134,0.9962919,0.000247612,0.001892894],"genre_scores_gemma":[0.001448323,0.0007620957,0.0008668185,0.0002190747,0.00002279385,0.0001711313,0.9949301,0.00008802929,0.001491628],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07163935,"threshold_uncertainty_score":0.2396575,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01776440386625678,"score_gpt":0.4457060108490556,"score_spread":0.4279416069827988,"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."}}