{"id":"W4233750564","doi":"10.1515/iupac.88.1197","title":"Phytoestrogen","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Phytoestrogen effects and research","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; 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":[0.001152884,0.001286799,0.001404933,0.004471308,0.0006495152,0.002169252,0.001689722,0.001522938,0.09831724],"category_scores_gemma":[0.009732961,0.0005447837,0.001744332,0.007913968,0.0003284079,0.001668619,0.001918926,0.001572733,0.07211708],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001263317,"about_ca_system_score_gemma":0.002927252,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0160685,"about_ca_topic_score_gemma":0.03271214,"domain_scores_codex":[0.9986394,0.0002348823,0.0003563232,0.0003685785,0.0002762669,0.0001244753],"domain_scores_gemma":[0.9959746,0.001388215,0.0006504319,0.0007341051,0.001040091,0.0002126182],"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":[0.0002027707,0.00002588523,0.002144044,0.006526161,0.0001134316,0.0000511295,0.00004731015,0.0002196878,0.0003029026,0.001203904,0.9747118,0.014451],"study_design_scores_gemma":[0.0001584423,0.00001823419,0.004941859,0.001671305,0.00007565186,0.00008597106,0.00005403203,0.00009126767,0.0001998428,0.0009454216,0.9917355,0.00002243275],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001063737,0.0003165992,0.00008082396,0.00008105869,0.00003434297,0.00002174918,0.9979867,0.0001030689,0.001269295],"genre_scores_gemma":[0.0004224943,0.0004622578,0.0004097481,0.0001800572,0.00001498815,0.0001409497,0.997113,0.0000407944,0.001215708],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09831724,"threshold_uncertainty_score":0.3289039,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02789842662154125,"score_gpt":0.4965921950548971,"score_spread":0.4686937684333559,"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."}}