{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003164845,0.003175937,0.002107873,0.003723767,0.0009892206,0.002784657,0.003054041,0.002071535,0.03429835],"category_scores_gemma":[0.01103563,0.0006643723,0.002605065,0.004085881,0.0006306022,0.001417415,0.002395144,0.00195578,0.05999148],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001643701,"about_ca_system_score_gemma":0.004425245,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008320537,"about_ca_topic_score_gemma":0.01795249,"domain_scores_codex":[0.9963581,0.0006620889,0.0006259837,0.001338676,0.0007026374,0.0003124576],"domain_scores_gemma":[0.9954163,0.001450449,0.000524959,0.001024589,0.001424885,0.0001587494],"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":[0.001092483,0.0001391909,0.006089163,0.008233096,0.000443057,0.0001454598,0.00006454755,0.001103221,0.002196428,0.00164304,0.918608,0.06024244],"study_design_scores_gemma":[0.0004594544,0.0001024968,0.006867766,0.001068093,0.0002465874,0.0002453905,0.00007060113,0.001080394,0.003386439,0.00331586,0.9830945,0.00006233654],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0009680079,0.001397958,0.002523822,0.0002060342,0.0001394849,0.0002795481,0.9897594,0.002199205,0.002526529],"genre_scores_gemma":[0.001564948,0.0006597862,0.004260913,0.0002254587,0.00003582111,0.0006679166,0.9906766,0.0001878138,0.00172066],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03429835,"threshold_uncertainty_score":0.1147394,"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."}}