{"id":"W4236179092","doi":"10.1515/iupac.78.0560","title":"Slimicide","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; Computer science; Pesticide; Management science; Data science; Ecology; Chemistry; 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":[0.001135458,0.001465018,0.001298288,0.005599496,0.0008192026,0.002708727,0.002586033,0.001609803,0.133178],"category_scores_gemma":[0.01007505,0.0004765159,0.001241805,0.01013377,0.0004067908,0.002062202,0.001938071,0.001635167,0.1198128],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001870888,"about_ca_system_score_gemma":0.003624445,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02080689,"about_ca_topic_score_gemma":0.04849553,"domain_scores_codex":[0.9986576,0.0002463937,0.0002841599,0.0003860193,0.0002890102,0.0001367658],"domain_scores_gemma":[0.9965513,0.001199417,0.0005347896,0.0005737042,0.0008783581,0.000262387],"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":[0.00006079589,0.00001096598,0.0007072066,0.001506768,0.00002440333,0.00002017864,0.00002426143,0.000130466,0.00007446794,0.0007369504,0.9931973,0.003506168],"study_design_scores_gemma":[0.000109811,0.00001102037,0.001758738,0.0006324103,0.00002262006,0.00003619683,0.00005367928,0.0001127354,0.0001001448,0.0009248463,0.9962229,0.00001498046],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005149702,0.0001065911,0.00004137195,0.00007010678,0.00001532042,0.00001291108,0.9987502,0.0001209766,0.0008310064],"genre_scores_gemma":[0.0002612433,0.0001470386,0.0002544368,0.0001119926,0.000008090497,0.0001378424,0.9981828,0.00005578446,0.0008408074],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.133178,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01129356420808756,"score_gpt":0.3507772451776613,"score_spread":0.3394836809695737,"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."}}