{"id":"W4237765533","doi":"10.1515/iupac.81.0811","title":"Secondary Substrate Metabolism","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 Toronto","funders":"","keywords":"Glossary; Ecotoxicology; Relation (database); Ecology; Computer science; Environmental chemistry; Biology; Chemistry; Data mining; Philosophy; 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":[0.0006954335,0.002612022,0.001902294,0.003267875,0.001051673,0.003730122,0.002148978,0.00182306,0.05797413],"category_scores_gemma":[0.003520804,0.0007268674,0.002104231,0.005976337,0.0003184061,0.001846128,0.001938963,0.00195275,0.1011758],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001819648,"about_ca_system_score_gemma":0.002503455,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01374202,"about_ca_topic_score_gemma":0.02703488,"domain_scores_codex":[0.9991516,0.000101467,0.0001180535,0.0002865808,0.0002045723,0.0001376854],"domain_scores_gemma":[0.9981926,0.000357744,0.000290909,0.0005049999,0.0004576615,0.0001961171],"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":[0.0005615823,0.00007541526,0.007897666,0.00434795,0.0001796932,0.0001444973,0.00005104565,0.001190333,0.001555873,0.001775812,0.9671497,0.01507034],"study_design_scores_gemma":[0.0001643208,0.00003908974,0.009729265,0.0006955407,0.0001004268,0.0002464082,0.0000518052,0.0006651513,0.001259756,0.002641317,0.9843604,0.00004655632],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003269082,0.0004235829,0.00009184167,0.00005274541,0.00002130276,0.00001040546,0.9974352,0.000235199,0.001402905],"genre_scores_gemma":[0.0004959036,0.0002224236,0.0002240988,0.00003193483,0.000003006972,0.00002393805,0.9985029,0.0000260601,0.0004697192],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.05797413,"threshold_uncertainty_score":0.1939428,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01071829937590183,"score_gpt":0.3309406433219755,"score_spread":0.3202223439460736,"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."}}