{"id":"W4413894363","doi":"10.1002/adhm.202502630","title":"Co‐Delivery of Ca‐MOF and Mg‐MOF Using Nanoengineered Hydrogels to Promote In Situ Mineralization and Bone Defect Repair: In Vitro and In Vivo Analysis","year":2025,"lang":"en","type":"article","venue":"Advanced Healthcare Materials","topic":"Bone Tissue Engineering Materials","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Institute of Musculoskeletal Health and Arthritis; Natural Sciences and Engineering Research Council of Canada; Ministry of Science and ICT, South Korea; Canadian Institutes of Health Research; Ministry of SMEs and Startups; National Research Foundation of Korea; Canada Research Chairs; National Research Foundation","keywords":"Self-healing hydrogels; Biocompatibility; Osseointegration; Materials science; Biomedical engineering; Drug delivery; Bone healing; In vivo; Scaffold; Nanotechnology; Implant; Surgery; 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004820404,0.0002541943,0.0009096161,0.00101786,0.00001955734,0.00002523114,0.00005061259,0.0001438755,0.000007283015],"category_scores_gemma":[0.00008121183,0.0003007053,0.00003091878,0.0008689082,0.00002382908,0.0001922569,0.00004633825,0.00007219752,2.801253e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001687818,"about_ca_system_score_gemma":0.0000227737,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001380226,"about_ca_topic_score_gemma":0.001865866,"domain_scores_codex":[0.9982815,0.0001038991,0.000803401,0.0003646157,0.0001006203,0.0003459986],"domain_scores_gemma":[0.9995307,0.00005891968,0.00006936551,0.0002228383,0.00003685213,0.00008130477],"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":[0.0001279583,0.00001188101,0.001207065,0.001560012,0.00004361015,0.00001796047,0.0004172836,0.061409,0.9349045,0.00003149379,0.000003252494,0.0002660384],"study_design_scores_gemma":[0.001023725,0.00004323361,0.0126155,0.0006874687,0.00005869003,0.000006730734,0.00005457519,0.01205327,0.9730123,0.00007406924,0.00006796,0.0003024206],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9963254,0.002056161,0.0003912101,0.00005794575,0.0001567773,0.0007186733,0.0001789854,0.0001090089,0.000005810729],"genre_scores_gemma":[0.9929522,0.0003613884,0.006507765,0.00002802562,0.00001337655,0.00005694052,0.00003249698,0.00003703246,0.00001074899],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04935573,"threshold_uncertainty_score":0.9999445,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008223368645872798,"score_gpt":0.2611104955370529,"score_spread":0.2528871268911801,"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."}}