{"id":"W3164871099","doi":"10.1021/acsami.1c02297","title":"Noninvasive Three-Dimensional <i>In Situ</i> and <i>In Vivo</i> Characterization of Bioprinted Hydrogel Scaffolds Using the X-ray Propagation-Based Imaging Technique","year":2021,"lang":"en","type":"article","venue":"ACS Applied Materials & Interfaces","topic":"3D Printing in Biomedical Research","field":"Engineering","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Light Source (Canada); University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Materials science; Scaffold; Biomedical engineering; 3D bioprinting; Characterization (materials science); Tissue engineering; In situ; Self-healing hydrogels; Structural integrity; 3D printing; Nanotechnology; Composite material; Chemistry","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":[0.0006552667,0.0001850999,0.000285312,0.0001597306,0.00004310497,0.00007783078,0.0001977728,0.0001002457,0.00008051914],"category_scores_gemma":[0.00005199695,0.0001564295,0.00001123024,0.0003511072,0.0001676412,0.00008275413,0.0001718473,0.0001203887,0.000003697423],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007326325,"about_ca_system_score_gemma":0.0000808434,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005337352,"about_ca_topic_score_gemma":0.00006544115,"domain_scores_codex":[0.9986272,0.00005331956,0.0004880632,0.0002806779,0.0002676221,0.0002830896],"domain_scores_gemma":[0.999418,0.0001330122,0.00009581471,0.0002400338,0.00007854689,0.00003465539],"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":[0.0000337118,0.00003358698,0.0003427876,0.0002033134,0.00001242089,0.00001363628,0.00006895637,0.001719662,0.9972485,0.00006610007,0.000003333696,0.0002540006],"study_design_scores_gemma":[0.000300412,0.000006657621,0.0005969999,0.0003735945,0.000007389694,0.000009647453,0.00003270488,0.002749775,0.9956198,0.0001441916,0.000009916184,0.0001488965],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9968221,0.00005895409,0.002125031,0.0001257394,0.0001191621,0.0005450901,0.00002923033,0.00006729828,0.0001074302],"genre_scores_gemma":[0.9983319,0.00001715175,0.001383429,0.00005681904,0.00002817493,0.0001172521,0.00002412275,0.0000371784,0.000003965749],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001628676,"threshold_uncertainty_score":0.6379011,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01032606855368776,"score_gpt":0.2377544084452659,"score_spread":0.2274283398915782,"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."}}