{"id":"W2180061851","doi":"10.1126/sciadv.1500417","title":"Fractal circuit sensors enable rapid quantification of biomarkers for donor lung assessment for transplantation","year":2015,"lang":"en","type":"article","venue":"Science Advances","topic":"Transplantation: Methods and Outcomes","field":"Medicine","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"University Health Network; University of Toronto","funders":"Canadian Institutes of Health Research","keywords":"Lung transplantation; Biomarker; Transplantation; Medicine; Lung; Profiling (computer programming); Clinical Practice; Gene expression profiling; Molecular biomarkers; Computational biology; Bioinformatics; Pathology; Gene expression; Computer science; Oncology; Internal medicine; Biology; Gene","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0005475709,0.0003694057,0.0003521971,0.000458947,0.000114184,0.0005021617,0.0003431449,0.0007490752,0.0008476804],"category_scores_gemma":[0.001154238,0.0002595289,0.000282809,0.0002511899,0.0003933185,0.0004701281,0.000279514,0.0006090205,0.0002553767],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003605577,"about_ca_system_score_gemma":0.0002358026,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002071992,"about_ca_topic_score_gemma":0.0003609882,"domain_scores_codex":[0.9996585,0.00008178222,0.00001591977,0.00005782765,0.0001546803,0.00003127575],"domain_scores_gemma":[0.9993594,0.000323906,0.0001100149,0.00005150819,0.0001236703,0.00003155757],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00007288312,0.00002831814,0.0009055965,0.00009978696,0.00001100972,0.00005069289,0.00004073871,0.001959478,0.975381,0.001193806,0.0003700815,0.0198865],"study_design_scores_gemma":[0.00001837153,0.0005200807,0.00357136,0.00002968905,0.00003270186,0.0004601346,0.00004860789,0.04962699,0.9372662,0.001458509,0.006909369,0.00005811952],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5568178,0.009205455,0.4242332,0.001494905,0.0006110365,0.0002535021,0.0009302633,0.001496957,0.004956909],"genre_scores_gemma":[0.8654975,0.002031077,0.1297506,0.0003556022,0.0001053854,0.0001576796,0.0002359456,0.00003695469,0.001829201],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008476804,"threshold_uncertainty_score":0.002895892,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0678532051074791,"score_gpt":0.4052447927859087,"score_spread":0.3373915876784296,"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."}}