{"id":"W4233494994","doi":"10.1515/iupac.78.0306","title":"Formulate","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; Management science; Data science; Chemistry; Engineering; 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":[0.001211256,0.002150057,0.00113237,0.004216705,0.001097633,0.003556662,0.002806258,0.001948804,0.2231878],"category_scores_gemma":[0.01020657,0.0006367912,0.001715275,0.006229023,0.0004255563,0.003360297,0.00245049,0.001902258,0.2549627],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002283613,"about_ca_system_score_gemma":0.003068941,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02394979,"about_ca_topic_score_gemma":0.04854782,"domain_scores_codex":[0.9981067,0.0002916743,0.0002901039,0.0006938511,0.0003922014,0.0002254467],"domain_scores_gemma":[0.9960877,0.001058577,0.0004026287,0.001014767,0.001189702,0.0002466888],"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":[0.00005140683,0.00001501879,0.000858793,0.0005373,0.00001856,0.0000178387,0.00002347255,0.0001487831,0.00007249794,0.0009528254,0.992281,0.005022615],"study_design_scores_gemma":[0.00007126234,0.00001036703,0.001735885,0.0003518295,0.0000154771,0.0000468822,0.00008467641,0.0002167575,0.0001416986,0.001916188,0.9953914,0.00001753505],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00009450996,0.00007699038,0.0001288278,0.0001066373,0.00002822707,0.00001826982,0.9974031,0.0002907249,0.001852767],"genre_scores_gemma":[0.0003010887,0.0000756303,0.0003801576,0.0001151046,0.000008595955,0.00009045738,0.9974808,0.00008778691,0.001460445],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7768122,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01704613565320914,"score_gpt":0.4266721422219049,"score_spread":0.4096260065686957,"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."}}