{"id":"W4242896458","doi":"10.1515/iupac.79.0841","title":"Aphicide","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Wildlife Conservation and Criminology Analyses","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Chemical nomenclature; Computer science; Toxicology; Chemistry; Philosophy; Biology; Linguistics; Organic chemistry","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":[0.00126832,0.001478679,0.001410441,0.004456356,0.0008198836,0.003269217,0.002274758,0.001309451,0.2272986],"category_scores_gemma":[0.01014221,0.0006555461,0.001455,0.007556955,0.0003387443,0.002298566,0.002023405,0.001746806,0.2828666],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001570358,"about_ca_system_score_gemma":0.003071024,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02045654,"about_ca_topic_score_gemma":0.03280582,"domain_scores_codex":[0.998071,0.0003171959,0.000354705,0.0005511048,0.0005159411,0.0001901622],"domain_scores_gemma":[0.9954435,0.001072206,0.0005389029,0.001201182,0.00146996,0.0002743209],"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":[0.00005232722,0.000009155323,0.0006585405,0.0005705985,0.00002140181,0.0000103087,0.00001204374,0.00007867316,0.00004038732,0.000486845,0.9932823,0.004777282],"study_design_scores_gemma":[0.00007720239,0.000006863867,0.00188028,0.0002713217,0.00001597427,0.00002447508,0.0000315752,0.00007735657,0.00008451776,0.0006770839,0.9968425,0.00001081892],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005226825,0.00006598516,0.00005354864,0.00006343207,0.00002842925,0.00001097647,0.9975472,0.0002718644,0.001906309],"genre_scores_gemma":[0.0002596904,0.0001139447,0.0002331909,0.0001062851,0.00001235278,0.00006208052,0.9968638,0.0001074161,0.002241198],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2272986,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02501489483792231,"score_gpt":0.3943717727856497,"score_spread":0.3693568779477274,"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."}}