{"id":"W4408385716","doi":"10.1002/nano.202400121","title":"Microfluidic Synthesis of Collagen‐Based Microgels for Tissue Engineering Applications","year":2025,"lang":"en","type":"article","venue":"Nano Select","topic":"3D Printing in Biomedical Research","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada; University of Toronto","funders":"National Research Council Canada; Natural Sciences and Engineering Research Council of Canada; University of Toronto; Sunnybrook Research Institute","keywords":"Microfluidics; Tissue engineering; Biomedical engineering; Nanotechnology; Materials science; Engineering","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":[0.0001440467,0.0002743796,0.00009835099,0.0001706469,0.00008937575,0.0002189638,0.0001127462,0.0002077378,0.0007381939],"category_scores_gemma":[0.0001677887,0.0001207581,0.0001638933,0.00009302024,0.0001024981,0.0001339349,0.000102348,0.0002072452,0.0002397634],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002115759,"about_ca_system_score_gemma":0.0001588022,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000228952,"about_ca_topic_score_gemma":0.0005953239,"domain_scores_codex":[0.9999484,0.000004884215,0.000005082298,0.00001437433,0.00001418013,0.00001307445],"domain_scores_gemma":[0.9999075,0.00003210724,0.00002780124,0.000007399258,0.00001083465,0.00001441238],"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":[0.000007950272,0.000005023963,0.00002151899,0.00002115432,0.000001152367,0.00001718661,0.0000056047,0.0001213426,0.9983788,0.00005934713,0.0000248158,0.00133612],"study_design_scores_gemma":[0.000009701194,0.00006639243,0.0004357123,0.000004354827,0.000003835055,0.00003648867,0.000005902754,0.001642053,0.9957415,0.00003628563,0.002013291,0.000004579828],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9056101,0.003694003,0.08425903,0.0002605373,0.0004384536,0.0002105608,0.000625985,0.0005308559,0.004370557],"genre_scores_gemma":[0.9411639,0.001142392,0.05457195,0.0001069491,0.00004349488,0.0001253155,0.0001882021,0.00004144133,0.002616296],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007381939,"threshold_uncertainty_score":0.00246954,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007239772514748887,"score_gpt":0.2670796170813206,"score_spread":0.2598398445665717,"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."}}