{"id":"W4235973655","doi":"10.1515/iupac.78.0415","title":"Micro-Environment","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; Pesticide; Computer science; Data science; Management science; Ecology; Engineering; Chemistry; Biology; Data mining","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":[0.0008042625,0.001866135,0.001213085,0.004281206,0.0009314371,0.002964645,0.002452833,0.001588957,0.1115391],"category_scores_gemma":[0.006317085,0.0005570243,0.001320524,0.009268412,0.0004037295,0.002635567,0.002620259,0.001845,0.1160311],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001796456,"about_ca_system_score_gemma":0.002798681,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03447963,"about_ca_topic_score_gemma":0.06500955,"domain_scores_codex":[0.9988295,0.000184132,0.0001963312,0.0003699615,0.0002651451,0.0001547956],"domain_scores_gemma":[0.9975593,0.0006666151,0.0003489537,0.0005673325,0.000644176,0.0002136449],"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":[0.00004159797,0.00001058864,0.001225812,0.00106911,0.00002999763,0.00002472921,0.00003635014,0.0002372876,0.00007684008,0.001173976,0.9923432,0.003730467],"study_design_scores_gemma":[0.00004177145,0.000005548024,0.002257485,0.0003623349,0.00001460433,0.0000364717,0.00005871553,0.0001152076,0.00008757822,0.001047367,0.9959583,0.00001460982],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005177495,0.00007932957,0.00005074618,0.00005044384,0.0000134179,0.000005846666,0.998835,0.0001254654,0.0007879334],"genre_scores_gemma":[0.000293472,0.0001189977,0.0002078827,0.00006937671,0.000005534789,0.00005473284,0.9984533,0.00004825538,0.0007484686],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1115391,"threshold_uncertainty_score":0.3731354,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01042685234276581,"score_gpt":0.3314052150210955,"score_spread":0.3209783626783297,"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."}}