{"id":"W4248335331","doi":"10.1515/iupac.78.0440","title":"Negative Resistance","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); Chemical nomenclature; Field (mathematics); Computer science; Pesticide; Data science; Management science; Ecology; Engineering; Biology; Chemistry; Data mining; Mathematics","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":[0.001035969,0.001727665,0.001424522,0.003859709,0.0009283118,0.002735028,0.002564286,0.00190909,0.1290626],"category_scores_gemma":[0.01099326,0.0005328112,0.001594321,0.006010956,0.000436183,0.002203422,0.001738292,0.001631091,0.0988376],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00137688,"about_ca_system_score_gemma":0.00228288,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01494652,"about_ca_topic_score_gemma":0.03456909,"domain_scores_codex":[0.9983475,0.000244962,0.0003287944,0.0005229497,0.0003653713,0.000190433],"domain_scores_gemma":[0.9958575,0.001478414,0.0006610139,0.0008591634,0.0009281986,0.0002156577],"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":[0.0000873134,0.00001687647,0.00199494,0.001410344,0.00003638515,0.00003371302,0.00002711765,0.0001916121,0.0001032221,0.0009124838,0.9899155,0.005270553],"study_design_scores_gemma":[0.0001420015,0.00001798215,0.005400465,0.00098007,0.0000476678,0.0001405459,0.00009509419,0.000204279,0.0001954952,0.002066746,0.99068,0.00002965406],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000175338,0.000174537,0.00007254342,0.00008503709,0.00002870395,0.00001510781,0.9977273,0.000132323,0.001589113],"genre_scores_gemma":[0.0007998794,0.0002142108,0.000300537,0.0001861335,0.00001278871,0.000116234,0.9968874,0.00005594927,0.001426813],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1290626,"threshold_uncertainty_score":0.4317574,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01061629532117214,"score_gpt":0.3453357001047491,"score_spread":0.3347194047835769,"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."}}