{"id":"W4251218720","doi":"10.1515/iupac.78.0625","title":"Trophic Level","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; Trophic level; Management science; Data science; Ecology; Engineering; 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":[0.0005343783,0.001558993,0.001270212,0.004564438,0.0006970512,0.002114885,0.00189133,0.001127605,0.1353066],"category_scores_gemma":[0.004943713,0.0005025297,0.001127903,0.009955256,0.0002962261,0.001714684,0.001585376,0.001467809,0.1110918],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001684813,"about_ca_system_score_gemma":0.002167579,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03363487,"about_ca_topic_score_gemma":0.05474713,"domain_scores_codex":[0.9992514,0.00008774085,0.0001490588,0.0002519752,0.0001610901,0.00009877772],"domain_scores_gemma":[0.9979962,0.0005420877,0.0003534588,0.0003274803,0.0006350426,0.000145776],"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":[0.00005937786,0.00001098505,0.001794485,0.001543646,0.00004015313,0.0000295884,0.00004702895,0.0002528569,0.0001235597,0.001130376,0.9899961,0.004971979],"study_design_scores_gemma":[0.00005621747,0.000007596166,0.004665753,0.0006543469,0.00002457607,0.00005439065,0.00007211262,0.0001006398,0.00008764049,0.001149981,0.9931103,0.00001644668],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005670918,0.00006504283,0.00002746006,0.00002212874,0.000008385659,0.000004768323,0.9990804,0.00004172033,0.0006933196],"genre_scores_gemma":[0.0003592913,0.0001254489,0.0001778354,0.00004623921,0.00000402338,0.0000491655,0.9984566,0.00002470672,0.0007566809],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1353066,"threshold_uncertainty_score":0.4526458,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02302649675136332,"score_gpt":0.3612565764837136,"score_spread":0.3382300797323503,"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."}}