{"id":"W4233227926","doi":"10.1515/iupac.83.0438","title":"Positive Assay Control","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Glossary; Context (archaeology); Field (mathematics); Process (computing); Multidisciplinary approach; Computer science; Data science; Component (thermodynamics); Management science; Sociology; Engineering; Biology; Linguistics; Mathematics; Social science","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":[0.005276744,0.002236879,0.002909105,0.004357141,0.001601632,0.004889286,0.004119733,0.002933488,0.1121532],"category_scores_gemma":[0.02436563,0.0009265738,0.002000142,0.004687902,0.001189066,0.001938622,0.002316201,0.003236717,0.1168816],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002144945,"about_ca_system_score_gemma":0.003857186,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007828271,"about_ca_topic_score_gemma":0.01384051,"domain_scores_codex":[0.9903193,0.001125231,0.001538559,0.00319322,0.002958677,0.0008650564],"domain_scores_gemma":[0.9835526,0.005836869,0.001642868,0.00461518,0.003774351,0.0005781113],"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":[0.0008182182,0.0001996648,0.007390918,0.003585439,0.0001287059,0.0001734144,0.00006279024,0.0006072453,0.002827908,0.003188187,0.9519715,0.02904619],"study_design_scores_gemma":[0.0002374999,0.00006905809,0.005863651,0.0006386662,0.0001089885,0.0003651118,0.00005558337,0.0004225333,0.003277939,0.002975306,0.9859247,0.00006094134],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001639235,0.001647582,0.002684447,0.0003492211,0.0004332264,0.0004356377,0.9788011,0.002230999,0.01177867],"genre_scores_gemma":[0.004224302,0.0006693478,0.00390975,0.0008918056,0.00007984916,0.001045685,0.983185,0.0005243879,0.005469863],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1121532,"threshold_uncertainty_score":0.3751898,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009329508200074218,"score_gpt":0.3736755681830744,"score_spread":0.3643460599830002,"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."}}