{"id":"W3007138159","doi":"10.1002/adfm.201903978","title":"Nonswelling, Ultralow Content Inverse Electron‐Demand Diels–Alder Hyaluronan Hydrogels with Tunable Gelation Time: Synthesis and In Vitro Evaluation","year":2020,"lang":"en","type":"article","venue":"Advanced Functional Materials","topic":"Advanced Sensor and Energy Harvesting Materials","field":"Engineering","cited_by":70,"is_retracted":false,"has_abstract":true,"ca_institutions":"Nipissing University; Canada Research Chairs; University Health Network; University of Toronto","funders":"Ontario Institute for Regenerative Medicine; University of Toronto","keywords":"Materials science; Self-healing hydrogels; In vitro; Inverse; Diels–Alder reaction; Chemical engineering; Nanotechnology; Polymer chemistry; Organic chemistry; Biochemistry","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":[0.0003080519,0.0003844597,0.0001163902,0.0001528291,0.00007772585,0.0002029055,0.0001623235,0.0002408145,0.0003579108],"category_scores_gemma":[0.0001671367,0.0001334662,0.000174822,0.0001514658,0.0001326647,0.00025719,0.0001153342,0.0002470627,0.0001172657],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002113301,"about_ca_system_score_gemma":0.0001003545,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002716408,"about_ca_topic_score_gemma":0.0005065425,"domain_scores_codex":[0.9998971,0.00001445295,0.00001049723,0.00002083363,0.00003977186,0.00001727969],"domain_scores_gemma":[0.9998068,0.00004330094,0.00008112774,0.00001347117,0.00002178627,0.00003347544],"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":[0.00001865807,0.00001462618,0.00002940338,0.00002860089,0.00000203317,0.0000155761,0.000008634501,0.00008771692,0.9991971,0.00001988462,0.000006800988,0.0005709725],"study_design_scores_gemma":[0.000003682869,0.0001236655,0.0003270758,0.000001989705,0.000005187648,0.00002303282,0.000003422913,0.0003233318,0.9989405,0.000006318273,0.0002387166,0.000002966482],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9900814,0.002177502,0.006695907,0.00003230438,0.00001573932,0.00003384554,0.0002444147,0.00004403211,0.0006749234],"genre_scores_gemma":[0.9893302,0.001152305,0.008052418,0.00002788538,0.000007513283,0.00003771777,0.0001890776,0.00002380482,0.001179008],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0003844597,"threshold_uncertainty_score":0.001629174,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02195499477663784,"score_gpt":0.2018053395763461,"score_spread":0.1798503447997082,"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."}}