{"id":"W4240583826","doi":"10.1515/iupac.88.0364","title":"Sequential Injection Analysis Extraction","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Medical Imaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; National Research Council Canada","funders":"","keywords":"Computer science; Extraction (chemistry); Sample (material); Scale (ratio); Process engineering; Chromatography; Chemistry; Engineering","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005237009,0.0002845558,0.0007155318,0.0004959251,0.0002440409,0.00009036576,0.0002427674,0.0004295108,0.003690323],"category_scores_gemma":[0.0005353801,0.0002487949,0.0004108854,0.0003592273,0.0001724982,0.00008094082,0.00008961501,0.0008924464,0.000003935921],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004047214,"about_ca_system_score_gemma":0.0005916405,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001171055,"about_ca_topic_score_gemma":0.0007101359,"domain_scores_codex":[0.9977846,0.00004029452,0.0004346703,0.0004984405,0.0009875252,0.0002545216],"domain_scores_gemma":[0.9974004,0.00002991181,0.0004349755,0.001405101,0.0004834173,0.0002461963],"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":[0.00008281584,0.000307974,0.00004290013,0.0001084954,0.0006421127,0.00005704083,0.000002705209,0.000001967246,0.00008272518,0.000003636366,0.9961386,0.002529049],"study_design_scores_gemma":[0.000425514,0.0001774089,0.0002519448,0.0001692836,0.005376006,0.00009037341,0.000006222994,0.00033452,0.00005931623,0.000057843,0.9928384,0.0002131809],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002172589,0.0001034176,0.009202695,0.002395169,0.0003048931,0.0004163502,0.9871191,0.0001671978,0.00007390958],"genre_scores_gemma":[0.0003210647,0.0005964342,0.00124241,0.0002991888,0.001232571,0.00005070324,0.9953679,0.00002436496,0.0008653362],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.008248817,"threshold_uncertainty_score":0.9999964,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0325017414766802,"score_gpt":0.5060297035340866,"score_spread":0.4735279620574064,"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."}}