{"id":"W4231785297","doi":"10.1515/iupac.88.0276","title":"Immunosorbents","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Immunodeficiency and Autoimmune Disorders","field":"Immunology and Microbiology","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 preparation; Sample (material); Process engineering; Chromatography; Biochemical engineering; 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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002213422,0.002512663,0.002292424,0.005127763,0.001212052,0.004303491,0.002923254,0.002696825,0.129877],"category_scores_gemma":[0.01633142,0.0006962814,0.00197176,0.007965543,0.0004308883,0.00232328,0.002687771,0.002289605,0.1495037],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001967221,"about_ca_system_score_gemma":0.004416596,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009741337,"about_ca_topic_score_gemma":0.01629545,"domain_scores_codex":[0.9963315,0.0006102187,0.0006721386,0.001096485,0.0008603033,0.0004294227],"domain_scores_gemma":[0.9936795,0.002081628,0.001020923,0.001158678,0.001684076,0.0003751578],"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":[0.0006080924,0.00005220796,0.00427371,0.007440084,0.0001800076,0.00007125122,0.00004936562,0.0003736602,0.0005224928,0.001762146,0.9618683,0.02279865],"study_design_scores_gemma":[0.0002826373,0.00003756868,0.005152181,0.001351536,0.0001024462,0.0001187684,0.00006621877,0.0001950974,0.0004733842,0.001996454,0.9901977,0.00002610235],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000207298,0.0006286248,0.0001818429,0.0001279372,0.00004911237,0.0000375378,0.9961864,0.0003819872,0.002199165],"genre_scores_gemma":[0.0007775945,0.000620664,0.0006711017,0.0002500458,0.00002567065,0.0001574475,0.996027,0.00008223231,0.001388235],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.870123,"threshold_uncertainty_score":0.4344817,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01241701474863812,"score_gpt":0.3886604159992118,"score_spread":0.3762434012505737,"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."}}