{"id":"W4220893296","doi":"10.1021/acsami.2c01741","title":"In Vitro Evaluation of Real-Time Viscoelastic and Coagulation Properties of Various Classes of Topical Hemostatic Agents Using a Novel Contactless Nondestructive Technology","year":2022,"lang":"en","type":"article","venue":"ACS Applied Materials & Interfaces","topic":"Hemostasis and retained surgical items","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Montreal General Hospital; McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Foundation for Innovation","keywords":"Biomedical engineering; Clotting time; Materials science; Viscoelasticity; Coagulation; Blood clotting; Activated clotting time; In vitro; Nanotechnology; Composite material; Surgery; Medicine; Chemistry; Anticoagulant; Internal medicine","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":[0.0004271342,0.0001043273,0.0005315434,0.0001625363,0.00002740675,0.000005811098,0.00005889643,0.00007252746,0.000110404],"category_scores_gemma":[0.0000703636,0.00008308356,0.00001025805,0.0001549692,0.000168759,0.00003876833,0.0001148914,0.00006654329,2.834136e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008866399,"about_ca_system_score_gemma":0.00009198449,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001835347,"about_ca_topic_score_gemma":0.000002353274,"domain_scores_codex":[0.9987919,0.00007699222,0.0005424628,0.0001704869,0.0003057346,0.0001124652],"domain_scores_gemma":[0.9993725,0.00005255988,0.0003062793,0.000118052,0.0001331238,0.00001745892],"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":[0.00108298,0.000189567,0.0001596306,0.0002438993,0.00006048818,0.000001269857,0.0008740812,0.0002599771,0.9961492,0.0004050546,7.922899e-7,0.0005730022],"study_design_scores_gemma":[0.001527584,0.0001976132,0.000724027,0.0001192655,0.0001321994,0.00002261645,0.001701199,0.0008510991,0.9942999,0.0003547001,0.000001646738,0.00006814754],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9989609,0.00006696633,0.00003965319,0.00007251184,0.00006330866,0.0006541167,0.00004338456,0.000007891116,0.00009124847],"genre_scores_gemma":[0.9993632,0.000009327363,0.0005351274,0.000009397259,0.000006965336,0.00004456477,0.00001293472,0.00001134004,0.00000708235],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001849356,"threshold_uncertainty_score":0.3388049,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0507617446931144,"score_gpt":0.3127460566457172,"score_spread":0.2619843119526028,"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."}}