{"id":"W4366237310","doi":"10.1073/pnas.2220565120","title":"DNA hydrogels for bone regeneration","year":2023,"lang":"en","type":"article","venue":"Proceedings of the National Academy of Sciences","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Government of Canada","keywords":"Self-healing hydrogels; Biomaterial; Regeneration (biology); Biophysics; Biomedical engineering; Tissue engineering; Chemistry; Cell biology; Osteoblast; Bone healing; Materials science; Fluorescence microscope; In vitro; Nanotechnology; Biochemistry; Anatomy; Biology; Fluorescence; Polymer chemistry; 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":[0.0006868021,0.00004864872,0.00007038152,0.0000735733,0.0001161019,0.000007700999,0.000208596,0.00006533707,2.116105e-7],"category_scores_gemma":[0.0003211975,0.00003221778,0.00007408107,0.0004116287,0.0002630484,0.000009509793,0.00006214959,0.00002687161,1.945035e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005096337,"about_ca_system_score_gemma":0.00001226289,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":3.788331e-7,"about_ca_topic_score_gemma":4.743275e-8,"domain_scores_codex":[0.9993036,0.000001931053,0.0001565671,0.0001624212,0.0002919525,0.0000834875],"domain_scores_gemma":[0.9995963,0.00001409731,0.0001840155,0.000006120802,0.0001876931,0.00001177864],"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":[0.000007428683,0.000007124588,0.0001375661,0.00001103416,0.000007014303,6.216326e-10,0.000005475521,0.00002412838,0.9930887,0.003518624,0.002647112,0.0005458433],"study_design_scores_gemma":[0.00005695148,0.00004565778,0.0006830726,0.00001361933,0.00000651135,0.000002191127,0.00002271876,0.0005660124,0.9816684,0.01520165,0.001691125,0.00004215631],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9968803,0.00005008649,0.00002854912,0.002227277,0.000007869041,0.0001209297,0.00001866948,0.00001408736,0.0006522534],"genre_scores_gemma":[0.9942151,0.0000556704,0.005125518,0.0001497183,0.00009615033,0.000008330826,0.00000179587,0.000002673269,0.0003450097],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01168303,"threshold_uncertainty_score":0.1313803,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0346022205650451,"score_gpt":0.3279948283096614,"score_spread":0.2933926077446163,"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."}}