{"id":"W4236685766","doi":"10.1515/iupac.78.0341","title":"GPC","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"","field":"","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; Engineering; Chemistry; 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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001022085,0.001600898,0.001246683,0.006419444,0.0009430894,0.002833571,0.002829131,0.001861102,0.1772954],"category_scores_gemma":[0.01032126,0.0005949456,0.001258024,0.01324752,0.000409367,0.002620514,0.002272088,0.00195475,0.1939338],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002125078,"about_ca_system_score_gemma":0.003846841,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03761748,"about_ca_topic_score_gemma":0.0558072,"domain_scores_codex":[0.9985353,0.0002299542,0.0002543485,0.0004758421,0.0003323765,0.0001722563],"domain_scores_gemma":[0.9962359,0.001069437,0.0004330828,0.0007358266,0.001258029,0.0002677123],"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":[0.00002761357,0.000007569864,0.0004174198,0.0006358615,0.00001394841,0.00001283088,0.00001817777,0.0001308198,0.00004952113,0.0006770861,0.9952133,0.002795962],"study_design_scores_gemma":[0.00006644223,0.000006568416,0.001585514,0.0004389424,0.00001491814,0.00003167982,0.00005244297,0.0001464771,0.00008343895,0.001184123,0.9963743,0.00001507797],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003655944,0.00004400008,0.00004485148,0.00004933235,0.00001173879,0.000008257191,0.9989704,0.0001204782,0.0007143071],"genre_scores_gemma":[0.0001555272,0.0000690169,0.0001908233,0.00005783282,0.000005310843,0.00006651916,0.9987102,0.0000567428,0.0006880641],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8227046,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01685648664367375,"score_gpt":0.4296934145617453,"score_spread":0.4128369279180716,"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."}}