{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002779607,0.0006560457,0.0002277458,0.0002881709,0.0001249068,0.0003854581,0.0003078748,0.000350953,0.0005396156],"category_scores_gemma":[0.0002813739,0.0002560159,0.0002822022,0.0001718202,0.0004383633,0.0004079885,0.0002397273,0.0003966253,0.0002427773],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002262772,"about_ca_system_score_gemma":0.0002137434,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003404203,"about_ca_topic_score_gemma":0.0006722452,"domain_scores_codex":[0.9998398,0.00001954598,0.0000114499,0.00004793103,0.00005816549,0.00002308004],"domain_scores_gemma":[0.9995494,0.0001565842,0.000184311,0.00005494279,0.00003423953,0.00002051856],"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":[0.000007809967,0.000004140648,0.00005953326,0.00002440595,0.000001473627,0.00001772052,0.000009834664,0.0001076442,0.9987848,0.00003660557,0.00001018007,0.0009358455],"study_design_scores_gemma":[0.000001116205,0.00003082016,0.0005211917,0.000001627899,0.000002950581,0.00007359078,0.000004736811,0.0007318461,0.9983391,0.00001419658,0.0002754967,0.000003362531],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8549534,0.003732251,0.1360559,0.0001308704,0.00005761317,0.00009382082,0.0004423866,0.0006089474,0.003924857],"genre_scores_gemma":[0.9025335,0.002465495,0.09195272,0.0000895047,0.00003750161,0.00009704133,0.00035892,0.0001527052,0.002312494],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0006560457,"threshold_uncertainty_score":0.001805127,"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."}}