{"id":"W2793823017","doi":"10.1002/advs.201700560","title":"Enabling Angioplasty‐Ready “Smart” Stents to Detect In‐Stent Restenosis and Occlusion","year":2018,"lang":"en","type":"article","venue":"Advanced Science","topic":"Coronary Interventions and Diagnostics","field":"Medicine","cited_by":114,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vancouver General Hospital; University of British Columbia","funders":"Canada Foundation for Innovation; British Columbia Knowledge Development Fund; CMC Microsystems; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Canadian Institutes of Health Research","keywords":"Restenosis; Angioplasty; Stent; Occlusion; Medicine; Balloon; Radiology; Cardiology","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":[0.0001898843,0.000246657,0.0002292705,0.0002749164,0.00007864153,0.0002536229,0.0002029026,0.0005201242,0.0004707577],"category_scores_gemma":[0.0003754672,0.0002215194,0.0001624567,0.0001289352,0.0001668428,0.0003352523,0.0002376525,0.0001712762,0.0002799816],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007175433,"about_ca_system_score_gemma":0.0000861728,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006913344,"about_ca_topic_score_gemma":0.0001952907,"domain_scores_codex":[0.9998587,0.00002504512,0.000009223113,0.00003172195,0.00006095033,0.00001435478],"domain_scores_gemma":[0.9998749,0.00003316705,0.00004178466,0.00001347962,0.00002433708,0.00001223712],"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":[0.00008964143,0.00002278655,0.001592738,0.00005030035,0.000009694449,0.00009426182,0.00002179105,0.0002090233,0.9803756,0.0002645479,0.000186863,0.01708275],"study_design_scores_gemma":[0.00002186277,0.0008069164,0.01353259,0.00001372899,0.00007080034,0.001293877,0.00002805403,0.01441375,0.9630933,0.0003220721,0.006369531,0.00003361081],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8494797,0.002261263,0.1444383,0.0002918672,0.0001729059,0.00009661567,0.0002151075,0.0008257733,0.002218437],"genre_scores_gemma":[0.9239632,0.0009007903,0.07283127,0.0002762941,0.00008871914,0.00006968575,0.0001395631,0.00002488089,0.00170563],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0005201242,"threshold_uncertainty_score":0.001574814,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02269332809592365,"score_gpt":0.3239303619320129,"score_spread":0.3012370338360892,"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."}}