{"id":"W1539956944","doi":"10.1111/j.1423-0410.2007.00967.x","title":"Detection of bacterial contamination of platelet concentrates","year":2007,"lang":"en","type":"article","venue":"Vox Sanguinis","topic":"Inflammatory Biomarkers in Disease Prognosis","field":"Medicine","cited_by":56,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canadian Blood Services","funders":"","keywords":"Library science; Philosophy; Computer 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":[0.0006376739,0.0004575023,0.0003118502,0.0009302021,0.0002260549,0.0006459853,0.0002120137,0.0006155167,0.001311512],"category_scores_gemma":[0.002051852,0.0002319056,0.0002084812,0.0004705884,0.0003046696,0.0001813427,0.0003777706,0.0004173709,0.0005899706],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009837969,"about_ca_system_score_gemma":0.0001905319,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004022942,"about_ca_topic_score_gemma":0.0002904384,"domain_scores_codex":[0.9986234,0.0004187813,0.0001068711,0.0001176935,0.0005444491,0.0001889076],"domain_scores_gemma":[0.9993488,0.0002793741,0.00009379671,0.00004434896,0.0001544086,0.00007925971],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0008554703,0.00009968874,0.04931174,0.0001710509,0.00006649314,0.001168211,0.0004056785,0.00008936842,0.9345683,0.0001340267,0.0002203168,0.01290949],"study_design_scores_gemma":[0.0000358496,0.001703386,0.1096024,0.000118259,0.0001737548,0.007220676,0.0005654241,0.002013089,0.8751596,0.0001988298,0.003193508,0.00001524089],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9875777,0.003957882,0.005016942,0.0002036469,0.00008524011,0.00007335337,0.000300933,0.00006858753,0.002715766],"genre_scores_gemma":[0.9937982,0.00121113,0.003304203,0.0001344707,0.00005056353,0.00003589145,0.0004590726,0.00001405444,0.0009922596],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001311512,"threshold_uncertainty_score":0.004387438,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009567716536172631,"score_gpt":0.2615659721621668,"score_spread":0.2519982556259941,"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."}}