{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000830345,0.0000551654,0.0001159001,0.00006882833,0.00001240539,0.000003863119,0.00006583817,0.000131452,0.00003503161],"category_scores_gemma":[0.0004713533,0.0000376676,0.00003921333,0.0001472224,0.00005847894,0.0000525996,0.00001499767,0.00005855882,0.0001183692],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001196329,"about_ca_system_score_gemma":0.000004130943,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001832925,"about_ca_topic_score_gemma":9.277433e-7,"domain_scores_codex":[0.999514,0.00001334128,0.0002170792,0.00009032128,0.00005788785,0.0001073635],"domain_scores_gemma":[0.9995067,0.000269541,0.00002267817,0.0001451014,0.00002862366,0.00002739205],"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":[0.000008485841,0.00005918413,0.01551506,0.00004158057,0.00005096223,0.000005028304,0.000008086849,0.0001248488,0.8380622,0.01058823,0.001172417,0.1343639],"study_design_scores_gemma":[0.0004309732,0.000149845,0.008046314,0.00009568934,0.00003069662,0.000004622612,0.00001006179,0.001545692,0.9763688,0.007215943,0.005954469,0.0001469104],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9890926,0.00006684026,0.009726983,0.00036303,0.000270503,0.00004377877,0.000004622608,0.0001502428,0.0002813484],"genre_scores_gemma":[0.999447,0.0002638155,0.0001394154,0.000008932324,0.00006081436,0.000003114199,7.266249e-7,0.000009854434,0.00006626174],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1383066,"threshold_uncertainty_score":0.153604,"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."}}