{"id":"W4250434247","doi":"10.1515/iupac.81.0687","title":"Phytoestrogen","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Pesticide and Herbicide Environmental Studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Ecotoxicology; Environmental risk assessment; Relation (database); Ecology; Computer science; Risk assessment; Biology; Data mining; Linguistics; 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":[0.0008289294,0.001338126,0.001207901,0.00327458,0.0006474736,0.001899555,0.001778408,0.00157688,0.07878114],"category_scores_gemma":[0.005531468,0.0004928436,0.00119829,0.005462258,0.0002596158,0.001363155,0.001463308,0.001655219,0.0787334],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001410741,"about_ca_system_score_gemma":0.002173838,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02063516,"about_ca_topic_score_gemma":0.04970871,"domain_scores_codex":[0.999041,0.0001501495,0.0001578754,0.000281243,0.0002525452,0.0001170118],"domain_scores_gemma":[0.9976034,0.0006527997,0.0004151948,0.0005086498,0.0006661876,0.0001538921],"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":[0.0002171231,0.00004594942,0.003432223,0.002831923,0.00007485562,0.00004971464,0.0000296939,0.0003360948,0.0003259491,0.001000461,0.9799918,0.01166436],"study_design_scores_gemma":[0.0001357729,0.00002297109,0.006227287,0.0006026316,0.00004619192,0.0001071635,0.00004895012,0.0001601033,0.0003381921,0.0009666351,0.9913257,0.00001844906],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001611345,0.0001898091,0.00005254012,0.00007210899,0.00002034265,0.00001091903,0.9981828,0.0000805249,0.001229614],"genre_scores_gemma":[0.0004668862,0.0002213186,0.0002796302,0.0001098495,0.000006618299,0.00004304965,0.9976743,0.00002043153,0.001177927],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07878114,"threshold_uncertainty_score":0.2635491,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01082913658580215,"score_gpt":0.3495012026138736,"score_spread":0.3386720660280715,"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."}}