{"id":"W4252027950","doi":"10.1515/iupac.78.0450","title":"Organically Grown","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); Pesticide; Computer science; Management science; Data science; Chemistry; Ecology; Engineering; 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":[0.0008266569,0.001643868,0.001205916,0.004618328,0.0008318408,0.00237678,0.00242714,0.001261607,0.1119869],"category_scores_gemma":[0.005747011,0.0004734256,0.001143782,0.01024094,0.0004219639,0.002164886,0.001900394,0.001591345,0.1212649],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001725043,"about_ca_system_score_gemma":0.003004136,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02816873,"about_ca_topic_score_gemma":0.05931367,"domain_scores_codex":[0.998799,0.0001656489,0.0001895761,0.000419613,0.0002723208,0.0001539596],"domain_scores_gemma":[0.9977759,0.0005437362,0.0003750925,0.0004495743,0.0006684432,0.0001872109],"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":[0.00005588343,0.00001076693,0.000878237,0.0009671799,0.00002257714,0.00002020176,0.00002592147,0.0001205024,0.00009844384,0.000821295,0.993869,0.003109955],"study_design_scores_gemma":[0.00005575174,0.000006627901,0.002616321,0.0003940318,0.00001558926,0.00003722785,0.00006494696,0.00006733208,0.0001147586,0.0007359728,0.9958787,0.0000126898],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006485014,0.00008456327,0.00003544109,0.00003937391,0.00001379145,0.000006000641,0.9988537,0.00007354358,0.0008287095],"genre_scores_gemma":[0.0002309435,0.0001016626,0.0001315544,0.00005414027,0.000004961228,0.00004199333,0.9985567,0.00003107016,0.0008470215],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1119869,"threshold_uncertainty_score":0.3746334,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009747874595965714,"score_gpt":0.3382459551523959,"score_spread":0.3284980805564302,"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."}}