{"id":"W4243398454","doi":"10.1515/iupac.81.0703","title":"Polygenic Control","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"History and advancements in chemistry","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Ecotoxicology; Relation (database); Environmental risk assessment; Computer science; Ecology; Data 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":[0.003003528,0.001550723,0.001665582,0.002784106,0.001239405,0.003308942,0.00336259,0.001864298,0.09153873],"category_scores_gemma":[0.02265862,0.0004793608,0.002514316,0.004515741,0.0007274796,0.001530621,0.001722502,0.002360859,0.03627144],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001466785,"about_ca_system_score_gemma":0.002166375,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0239666,"about_ca_topic_score_gemma":0.02814665,"domain_scores_codex":[0.9970194,0.0006997844,0.000258744,0.00136068,0.0003604749,0.0003009474],"domain_scores_gemma":[0.9919345,0.00385933,0.0006949673,0.002303965,0.0008546227,0.0003526608],"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":[0.000423777,0.0001139007,0.03899724,0.001419109,0.0005407939,0.0002304517,0.000094812,0.002259778,0.0002988553,0.00905114,0.9171075,0.02946269],"study_design_scores_gemma":[0.0006089701,0.00009415534,0.03931662,0.0009276604,0.0005275427,0.0008034543,0.000168662,0.005139957,0.0005603933,0.0250222,0.9267316,0.00009875245],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00243584,0.0009859907,0.002516523,0.0004894049,0.0001953496,0.00007595071,0.9888399,0.0007180809,0.003743045],"genre_scores_gemma":[0.01189939,0.0005147854,0.00262895,0.000483321,0.0000821108,0.0003753161,0.9799544,0.0002060216,0.003855768],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09153873,"threshold_uncertainty_score":0.3062276,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00931928344023217,"score_gpt":0.3706417236203179,"score_spread":0.3613224401800857,"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."}}