{"id":"W4238301491","doi":"10.1515/iupac.78.0579","title":"Sticker","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Biomedical and Chemical Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Glossary; Chemical nomenclature; Relation (database); Computer science; Pesticide; Management science; Chemistry; Ecology; 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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003797377,0.0003141855,0.0006830727,0.0001624679,0.00004714746,0.00002001488,0.0002813782,0.0006473646,0.02735725],"category_scores_gemma":[0.002157538,0.0001807464,0.0002080539,0.000213005,0.0004410753,0.00002344699,0.0002263782,0.0009755894,0.00002735114],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003613418,"about_ca_system_score_gemma":0.001362819,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004300805,"about_ca_topic_score_gemma":0.00002763564,"domain_scores_codex":[0.9962199,0.00003272156,0.0003852166,0.0004683181,0.002325316,0.000568567],"domain_scores_gemma":[0.9977517,0.0001575786,0.00008077617,0.0007363017,0.000545231,0.0007284168],"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":[0.000455705,0.0003881505,0.000005590997,0.0004725098,0.0001277284,0.0003301819,0.000001298882,1.111387e-9,0.0001974369,0.000003596326,0.9825428,0.01547503],"study_design_scores_gemma":[0.001652244,0.0003949132,0.00002975819,0.0009640345,0.0001628184,0.00004969801,0.000004756693,0.000001091922,0.0001873827,0.0001578371,0.9961733,0.0002222022],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00007704776,0.0008051963,0.00004865458,0.006904186,0.0002758672,0.0002461669,0.991369,0.00005277674,0.0002210909],"genre_scores_gemma":[0.00001374074,0.001616859,0.00003836692,0.00120149,0.001960662,0.000012845,0.9910209,0.00003127259,0.004103904],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.0273299,"threshold_uncertainty_score":0.9735319,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02337004766255388,"score_gpt":0.4693685010344602,"score_spread":0.4459984533719063,"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."}}