{"id":"W2524593478","doi":"10.1002/adhm.201600720","title":"Strong and Rapidly Self‐Healing Hydrogels: Potential Hemostatic Materials","year":2016,"lang":"en","type":"article","venue":"Advanced Healthcare Materials","topic":"Hemostasis and retained surgical items","field":"Medicine","cited_by":178,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Alberta Innovates Bio Solutions; China Scholarship Council; Natural Sciences and Engineering Research Council of Canada; Alberta Crop Industry Development Fund","keywords":"Self-healing hydrogels; Self-healing; Hemostatic Agent; Materials science; Nanotechnology; Biomedical engineering; Hemostasis; Medicine; Polymer chemistry; Surgery; Pathology","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":[0.0001659209,0.0004174278,0.0001219017,0.0002414406,0.00006354121,0.0002018259,0.000193213,0.000330968,0.0007948505],"category_scores_gemma":[0.0001351585,0.0001435255,0.0001367725,0.0001291606,0.000114782,0.0003414501,0.000131438,0.0002749974,0.0002612357],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000169949,"about_ca_system_score_gemma":0.00008507202,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001101011,"about_ca_topic_score_gemma":0.00018885,"domain_scores_codex":[0.999923,0.00001567577,0.000004705036,0.00001320842,0.00002438394,0.00001907392],"domain_scores_gemma":[0.9998717,0.00002266619,0.00005697737,0.000006073913,0.00001419389,0.00002840035],"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":[0.00003556554,0.00002033306,0.00005595249,0.0000592584,0.000003023413,0.00003921641,0.000007048222,0.0001009564,0.9958797,0.0001329254,0.00006412013,0.003601955],"study_design_scores_gemma":[0.00001058477,0.0001748359,0.0007070237,0.000007111388,0.0000092937,0.0001923615,0.000005544358,0.0005783542,0.9961054,0.00004959044,0.002154562,0.000005437582],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9341664,0.02109012,0.03784017,0.0005645002,0.0001429666,0.0001252415,0.0004588376,0.0003821261,0.005229574],"genre_scores_gemma":[0.9814564,0.003413837,0.01190118,0.0001784351,0.00004369621,0.00005498942,0.0001558623,0.0000300135,0.002765591],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007948505,"threshold_uncertainty_score":0.002659082,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01883115359771134,"score_gpt":0.3058625354131829,"score_spread":0.2870313818154716,"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."}}