{"id":"W4408421038","doi":"10.1088/1748-605x/adc059","title":"Highly elastic bioactive bR-GelMA micro-particles: synthesis and precise micro-fabrication via stop-flow lithography","year":2025,"lang":"en","type":"article","venue":"Biomedical Materials","topic":"Innovative Microfluidic and Catalytic Techniques Innovation","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; University of Toronto; St. Michael's Hospital","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Toronto Metropolitan University","keywords":"Materials science; Fabrication; Nanotechnology; Self-healing hydrogels; Gelatin; Biomedical engineering; Lithography; Flexibility (engineering); Particle (ecology); Composite material; Optoelectronics; 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":[0.0004193862,0.0004264082,0.0001829431,0.0003848965,0.0001488812,0.0002284855,0.000287392,0.0004450502,0.0008711834],"category_scores_gemma":[0.0003534832,0.0003098799,0.0002312223,0.00008879918,0.0003535138,0.000262786,0.0002735492,0.0005079785,0.000655807],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002737313,"about_ca_system_score_gemma":0.00019798,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003089289,"about_ca_topic_score_gemma":0.0009472985,"domain_scores_codex":[0.9998035,0.00002105126,0.0000177846,0.00004821062,0.00008548827,0.00002404214],"domain_scores_gemma":[0.9996892,0.0001045389,0.0001275976,0.00003191398,0.00002810747,0.0000186053],"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":[0.000006631862,0.000006354141,0.0000263099,0.00002657257,0.000001153165,0.00001954199,0.00001154741,0.00007362745,0.9982032,0.0001283066,0.00003091079,0.001465828],"study_design_scores_gemma":[0.000008262034,0.00006293321,0.0003343607,0.000004668735,0.000002625633,0.00006974353,0.00000541133,0.001181801,0.9963927,0.00004014445,0.00189068,0.000006702729],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6700929,0.003627955,0.3148732,0.0005965089,0.0001733162,0.000490823,0.0005496582,0.00203938,0.007556132],"genre_scores_gemma":[0.733952,0.001098816,0.2595232,0.0001680324,0.00003469655,0.0004087078,0.00025822,0.0001584328,0.004397959],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008711834,"threshold_uncertainty_score":0.002914369,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006828271617057216,"score_gpt":0.2257721493808139,"score_spread":0.2189438777637567,"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."}}