{"id":"W4206362423","doi":"10.1073/pnas.2117232119","title":"Role of smooth muscle activation in the static and dynamic mechanical characterization of human aortas","year":2022,"lang":"en","type":"article","venue":"Proceedings of the National Academy of Sciences","topic":"Elasticity and Material Modeling","field":"Engineering","cited_by":42,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre Hospitalier de l’Université de Montréal; McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Government of Canada","keywords":"Isometric exercise; Viscoelasticity; Smooth muscle; Vascular smooth muscle; Characterization (materials science); Quasistatic process; Depolarization; Blood vessel","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":[0.0006241155,0.00003505609,0.00007532718,0.00008889961,0.00007134338,0.000005373908,0.0002214599,0.00001936989,0.000005534945],"category_scores_gemma":[0.00004818676,0.00002519453,0.00001341763,0.000276441,0.00009327165,0.0001850948,0.00005089015,0.00007580177,1.600146e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001553798,"about_ca_system_score_gemma":0.000005815053,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006915118,"about_ca_topic_score_gemma":1.387542e-7,"domain_scores_codex":[0.9992721,0.000006142848,0.0002068254,0.00006165892,0.0004038128,0.00004943773],"domain_scores_gemma":[0.9997585,0.00004313364,0.0001496537,0.000004111682,0.00003949032,0.000005148815],"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":[0.000002997217,0.00001515979,0.00009985827,0.00006186531,0.000001969728,2.826117e-10,0.0006163113,0.002442122,0.9766628,0.01987095,7.819924e-7,0.0002252539],"study_design_scores_gemma":[0.0001558757,0.0000779241,0.1205429,0.00008871798,0.000009941524,6.368195e-7,0.001254782,0.1400979,0.6673104,0.07038783,0.00001111561,0.00006191486],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9995505,0.000006317237,0.00002028179,0.0001774337,0.000006337613,0.00009229332,0.00001195214,0.00000383912,0.0001310676],"genre_scores_gemma":[0.999804,0.000005990476,0.0001527104,0.00001940374,0.000005839234,0.000008159957,5.43273e-7,0.000002100177,0.000001276914],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3093524,"threshold_uncertainty_score":0.1027403,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01952596653985281,"score_gpt":0.2570326599345434,"score_spread":0.2375066933946906,"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."}}