{"id":"W2553932322","doi":"10.1002/adhm.201670117","title":"Hydrogels: Strong and Rapidly Self‐Healing Hydrogels: Potential Hemostatic Materials (Adv. Healthcare Mater. 21/2016)","year":2016,"lang":"en","type":"article","venue":"Advanced Healthcare Materials","topic":"Hydrogels: synthesis, properties, applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Self-healing hydrogels; Chitosan; Polyethylene glycol; Self-healing; Hemostatic Agent; Materials science; Nanotechnology; Biomedical engineering; Chemistry; Polymer chemistry; Medicine; Hemostasis; Surgery; Organic chemistry","routes":{"ca_aff":true,"ca_fund":false,"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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008956089,0.0007030966,0.0009298357,0.0001476758,0.0005192403,0.0001493385,0.0005035624,0.0004930672,0.0001530424],"category_scores_gemma":[0.000156341,0.000569195,0.0001098955,0.0001453357,0.0002375932,0.00007085589,0.0003742807,0.0001214558,0.0001357569],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001780433,"about_ca_system_score_gemma":0.0003530954,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005472942,"about_ca_topic_score_gemma":0.00007926588,"domain_scores_codex":[0.9947419,0.0007128958,0.001434156,0.001409887,0.0003975224,0.001303637],"domain_scores_gemma":[0.997266,0.00005855054,0.0006221664,0.001237088,0.0002768038,0.0005393782],"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":[0.00035509,0.00007161143,0.0001223786,0.0006071476,0.00009228018,0.00001178509,0.0001572633,0.000008490992,0.9814532,0.0003861827,0.0001381497,0.01659635],"study_design_scores_gemma":[0.001296191,0.0004428597,0.0002310144,0.0004314517,0.00004930136,0.000126399,0.000202981,0.000004075866,0.9774955,0.000795104,0.01821553,0.0007096097],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9825101,0.002998453,0.001543395,0.008843462,0.0007593055,0.001700263,0.001354577,0.0002592154,0.00003122048],"genre_scores_gemma":[0.9855154,0.004170406,0.006776186,0.001376095,0.0005845088,0.0007178767,0.0003849452,0.000214544,0.0002600603],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01807738,"threshold_uncertainty_score":0.9996759,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0160435022918935,"score_gpt":0.2778723447506142,"score_spread":0.2618288424587207,"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."}}