{"id":"W2328480348","doi":"10.1021/acsnano.6b01254","title":"Clinical Validation of Quantum Dot Barcode Diagnostic Technology","year":2016,"lang":"en","type":"article","venue":"ACS Nano","topic":"Biosensors and Analytical Detection","field":"Engineering","cited_by":126,"is_retracted":false,"has_abstract":true,"ca_institutions":"University Health Network; University of Toronto","funders":"Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Barcode; Computer science; Quantum dot; Disruptive technology; Blueprint; Medical physics; Nanotechnology; Medicine; Engineering; Manufacturing engineering; Materials science","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":[0.01979302,0.000808134,0.0007437422,0.000782145,0.0007183631,0.001512546,0.001316899,0.00206176,0.001692266],"category_scores_gemma":[0.02473882,0.0004713354,0.000513578,0.0004565219,0.002278766,0.0007152815,0.001034668,0.001437585,0.001481171],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001017586,"about_ca_system_score_gemma":0.002034859,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001124062,"about_ca_topic_score_gemma":0.000733856,"domain_scores_codex":[0.9834637,0.008136001,0.001033398,0.00181833,0.005095878,0.0004526521],"domain_scores_gemma":[0.9869164,0.005271832,0.000862334,0.00175516,0.004853355,0.0003408547],"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":[0.003634816,0.001397645,0.04038098,0.00185356,0.0003127956,0.0009523069,0.00168451,0.003410604,0.7572337,0.007768141,0.00881039,0.1725607],"study_design_scores_gemma":[0.0003153909,0.008527138,0.01968752,0.0004387118,0.0002191629,0.003049994,0.0003831911,0.01296343,0.8930904,0.002450968,0.0587515,0.0001225974],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4463342,0.01405827,0.5025495,0.007313669,0.001786146,0.005147733,0.002501508,0.001743301,0.01856575],"genre_scores_gemma":[0.7704794,0.004295882,0.2093383,0.005351686,0.0002570955,0.002445788,0.002139347,0.0002920813,0.005400274],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01979302,"threshold_uncertainty_score":0.1046767,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01491514099351383,"score_gpt":0.2585569529589254,"score_spread":0.2436418119654116,"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."}}