{"id":"W1988741595","doi":"10.1021/nn503719n","title":"Shear-Thinning Nanocomposite Hydrogels for the Treatment of Hemorrhage","year":2014,"lang":"en","type":"article","venue":"ACS Nano","topic":"Hemostasis and retained surgical items","field":"Medicine","cited_by":399,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Brookhaven National Laboratory; Army Research Office; Health Canada; U.S. Public Health Service; National Institutes of Health; Fonds de Recherche du Québec - Santé; National Institute of General Medical Sciences; Deutsche Herzstiftung","keywords":"Hemostasis; Self-healing hydrogels; Hemostat; Materials science; Biomedical engineering; Fibrin; Nanocomposite; Gelatin; Shear thinning; Biocompatible material; Nanotechnology; Composite material; Surgery; Medicine; Chemistry; Rheology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001040915,0.0002536195,0.00008854686,0.0001808506,0.00007291501,0.0001201521,0.00008682037,0.0001741274,0.0005531565],"category_scores_gemma":[0.00005937432,0.00008480409,0.0001299021,0.00005983592,0.0000815243,0.0001537587,0.00008661413,0.000242014,0.00009146826],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001100479,"about_ca_system_score_gemma":0.00008535382,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001971203,"about_ca_topic_score_gemma":0.0005084421,"domain_scores_codex":[0.9999738,0.000003900989,0.000002143216,0.000005964521,0.000009240393,0.000004975082],"domain_scores_gemma":[0.9999654,0.000008434451,0.00001277838,0.000001274336,0.000004200822,0.000007897791],"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":[0.00003423015,0.00002159635,0.00003261175,0.00005484463,0.000003938761,0.00003538976,0.000007106414,0.0002035519,0.9962386,0.00006617898,0.00005907236,0.003242908],"study_design_scores_gemma":[0.00001389503,0.0002865184,0.0005923304,0.00001070248,0.00001740902,0.0001513011,0.000008797298,0.001866809,0.9946828,0.00004066472,0.002322384,0.000006415894],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9634941,0.01288849,0.01776003,0.0003187753,0.0001614865,0.0000707117,0.0001691704,0.00023071,0.004906514],"genre_scores_gemma":[0.986095,0.003795959,0.007752613,0.0001259222,0.00003312717,0.00003692492,0.00006606011,0.00001719295,0.002077267],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0005531565,"threshold_uncertainty_score":0.001850486,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02330501065968677,"score_gpt":0.285877478522604,"score_spread":0.2625724678629172,"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."}}