{"id":"W4238483144","doi":"10.1515/iupac.88.0712","title":"Ecogenetics","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Effects and risks of endocrine disrupting chemicals","field":"Environmental Science","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":[0.001602864,0.001443771,0.001499071,0.005794615,0.0009888719,0.003164046,0.002281188,0.001602761,0.1238862],"category_scores_gemma":[0.01276578,0.0007028426,0.001943952,0.01058174,0.0004735315,0.002199123,0.002921138,0.002155162,0.09448812],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001379187,"about_ca_system_score_gemma":0.003817461,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01749216,"about_ca_topic_score_gemma":0.03072371,"domain_scores_codex":[0.9981224,0.0003385619,0.000432799,0.0005581757,0.0003610516,0.0001871397],"domain_scores_gemma":[0.9943058,0.001993227,0.0007571947,0.001394276,0.001254895,0.0002946696],"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":[0.000102963,0.00001980415,0.003959213,0.004377865,0.0001077817,0.00007440841,0.00009029609,0.0002978559,0.0003127266,0.002524137,0.9750088,0.01312407],"study_design_scores_gemma":[0.00005964567,0.000008229411,0.004691196,0.0008782691,0.00004425952,0.00008092873,0.00006177182,0.00006757388,0.0001257185,0.001354558,0.9926099,0.00001784457],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001309263,0.0003087613,0.0001949773,0.0001036315,0.00004394001,0.00002179058,0.9968702,0.0002110229,0.002114809],"genre_scores_gemma":[0.0005354259,0.0004499202,0.0007397055,0.0001929783,0.00001513561,0.0001548711,0.9964014,0.0001141742,0.001396278],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1238862,"threshold_uncertainty_score":0.4144407,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01268652928285135,"score_gpt":0.4588810919993524,"score_spread":0.446194562716501,"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."}}