{"id":"W4243388782","doi":"10.1515/iupac.78.0494","title":"Precision","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; Data science; Management 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":[],"consensus_categories":[],"category_scores_codex":[0.002025881,0.0022175,0.001747773,0.006632964,0.001353396,0.004209057,0.0036516,0.00213714,0.1282082],"category_scores_gemma":[0.01745692,0.000725883,0.002280118,0.0107799,0.0006460764,0.003692839,0.00256319,0.00262359,0.1330754],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002322104,"about_ca_system_score_gemma":0.003274174,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02762184,"about_ca_topic_score_gemma":0.04595641,"domain_scores_codex":[0.9960619,0.0005374192,0.000796267,0.00145541,0.0008377979,0.0003111614],"domain_scores_gemma":[0.9931879,0.002042491,0.0008277366,0.001641235,0.002051546,0.0002490925],"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":[0.0000877746,0.0000226212,0.001780886,0.001177356,0.00005491442,0.00002843852,0.00005151024,0.0002603703,0.0001115689,0.001163785,0.9879255,0.007335213],"study_design_scores_gemma":[0.000139822,0.0000174251,0.004685351,0.0007947148,0.00004834031,0.0001049654,0.0001304151,0.0003378441,0.0002708417,0.002677142,0.9907417,0.00005152984],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001683846,0.0001481458,0.0001536473,0.0001043521,0.00003245984,0.00002415286,0.9978096,0.0002639288,0.001295283],"genre_scores_gemma":[0.0005976441,0.0001182975,0.0005564311,0.00009085351,0.00001330113,0.0001777619,0.997143,0.0001012579,0.001201387],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1282082,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01725852627004463,"score_gpt":0.4298294800574559,"score_spread":0.4125709537874113,"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."}}