{"id":"W4238661941","doi":"10.1515/iupac.78.0492","title":"Potentiation","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 Guelph","funders":"","keywords":"Glossary; Relation (database); Computer science; Pesticide; Chemical nomenclature; Chemistry; Ecology; Biology; Data mining; Linguistics","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":[0.001106014,0.001786668,0.001207626,0.004365067,0.0009319321,0.003153002,0.002442781,0.001899803,0.1757571],"category_scores_gemma":[0.009457395,0.0005343324,0.001441287,0.007881765,0.0003771098,0.002833785,0.00209708,0.001680931,0.1934474],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002029952,"about_ca_system_score_gemma":0.003112442,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01997028,"about_ca_topic_score_gemma":0.04045529,"domain_scores_codex":[0.9981153,0.000288758,0.0003281873,0.0006484177,0.0004007998,0.0002185179],"domain_scores_gemma":[0.9965981,0.0009240378,0.0004302587,0.0007286243,0.001074585,0.0002443667],"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":[0.00005176071,0.00001158465,0.0008402197,0.0008623169,0.000020471,0.00001871776,0.00002251175,0.0001129803,0.00007784637,0.0007997951,0.9933656,0.003816306],"study_design_scores_gemma":[0.00006807815,0.000009423153,0.001967943,0.0004454677,0.00001614625,0.00004660377,0.00005758794,0.0001101167,0.0001215886,0.001097317,0.9960437,0.00001603939],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005578425,0.00008284661,0.00005046949,0.00007370652,0.00002010941,0.00001173941,0.9984685,0.0001382374,0.00109864],"genre_scores_gemma":[0.0002311313,0.00009550795,0.0002144632,0.0001053905,0.000006948646,0.00007634184,0.9983029,0.00004748198,0.0009197007],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1757571,"threshold_uncertainty_score":0.5879659,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00934243176039843,"score_gpt":0.3421846783482222,"score_spread":0.3328422465878238,"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."}}