{"id":"W4230123126","doi":"10.1515/iupac.78.0238","title":"Degradation","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; Pesticide; Computer science; Relation (database); Chemical nomenclature; Environmental chemistry; Data science; Chemistry; Ecology; 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":[0.001237174,0.00184886,0.001227903,0.004470213,0.0008260774,0.003004913,0.002311517,0.001616807,0.1140149],"category_scores_gemma":[0.008596914,0.0005185439,0.00178558,0.007795359,0.0003759538,0.002559345,0.001835761,0.001569098,0.1147033],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002278936,"about_ca_system_score_gemma":0.00280079,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02726381,"about_ca_topic_score_gemma":0.04815783,"domain_scores_codex":[0.9980736,0.0002921928,0.0003542269,0.0006535685,0.00044508,0.000181359],"domain_scores_gemma":[0.9966027,0.000926693,0.0004986752,0.000730126,0.001067685,0.0001742035],"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":[0.00006028238,0.00001402415,0.001612313,0.001329869,0.0000389405,0.00002231154,0.00002957782,0.0002721417,0.0001149821,0.001151285,0.9887673,0.006586898],"study_design_scores_gemma":[0.00005807178,0.00001041263,0.003492366,0.0005972301,0.00002720604,0.00005363565,0.00006365444,0.0002088849,0.0001656179,0.001403848,0.9938983,0.0000207146],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00009838019,0.0001665392,0.00008326001,0.00008821535,0.00002219279,0.00001032649,0.9980156,0.0001467458,0.001368564],"genre_scores_gemma":[0.0004014061,0.0001664957,0.0002631072,0.00009589133,0.000006767836,0.000063468,0.9978924,0.00004700619,0.001063485],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1140149,"threshold_uncertainty_score":0.3814178,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.012581494928535,"score_gpt":0.3500185810781148,"score_spread":0.3374370861495798,"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."}}