{"id":"W4242105976","doi":"10.1515/iupac.78.0151","title":"Application Rate","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; Chemical nomenclature; Relation (database); Computer science; Pesticide; Management science; Data science; Chemistry; Ecology; Engineering; Data mining; Biology; 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":[0.002140763,0.001424356,0.001738373,0.005596608,0.0009685382,0.003583795,0.002576298,0.002153338,0.2235643],"category_scores_gemma":[0.0219708,0.0005215781,0.00163994,0.009284819,0.0003920599,0.003118892,0.002169384,0.002029717,0.2063269],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002141531,"about_ca_system_score_gemma":0.003632185,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01904109,"about_ca_topic_score_gemma":0.02503652,"domain_scores_codex":[0.9966244,0.0005734925,0.0007528142,0.001022955,0.00073398,0.0002924376],"domain_scores_gemma":[0.9909158,0.002932968,0.001055135,0.001599054,0.002965634,0.0005312957],"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":[0.00006429666,0.00001160712,0.0007783778,0.0008634763,0.00002259036,0.00001717306,0.00001638646,0.00009245448,0.00003935882,0.0005939665,0.9933195,0.004180938],"study_design_scores_gemma":[0.0001223976,0.00001048511,0.002431807,0.0006548158,0.00002428103,0.00004904252,0.00005071374,0.0001124889,0.00008892055,0.001050966,0.9953846,0.00001945732],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00008618267,0.0001444252,0.00006375903,0.0001482805,0.00005051529,0.00003284304,0.9971296,0.0001589318,0.002185478],"genre_scores_gemma":[0.0005303584,0.0002125145,0.0003171184,0.0002814777,0.00003559337,0.0002901897,0.9953948,0.0001064526,0.002831545],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2235643,"threshold_uncertainty_score":0.7478973,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008836183675706193,"score_gpt":0.34338036587534,"score_spread":0.3345441821996338,"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."}}