{"id":"W4416042421","doi":"10.1101/2025.11.06.687056","title":"Engineering a Multilayer Microfluidic Airway-On-A-Chip with Tunable GelMA Hydrogel for Physiologically Relevant Aerosol Exposure Studies","year":2025,"lang":"","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"3D Printing in Biomedical Research","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Mitacs","keywords":"Microfluidics; Self-healing hydrogels; Extracellular matrix; Aerosol; Gelatin; Airway; Cigarette smoke; Tissue 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":[0.0002232856,0.0003328181,0.0002003738,0.0001625993,0.0001095981,0.0002287611,0.0003344676,0.0003534248,0.0006236578],"category_scores_gemma":[0.0001985824,0.0001545705,0.0002518174,0.0000688227,0.0001394528,0.0002533447,0.0003084498,0.0003015208,0.0002285302],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002703902,"about_ca_system_score_gemma":0.00024199,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002984597,"about_ca_topic_score_gemma":0.0006345486,"domain_scores_codex":[0.9998778,0.000010471,0.000009570895,0.00003742839,0.00003609133,0.00002865533],"domain_scores_gemma":[0.9998814,0.0000345009,0.00003267776,0.00001360727,0.00001927431,0.00001848857],"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":[0.000007690593,0.00001582938,0.00007346675,0.00003355856,0.000003104094,0.00002477008,0.000007117114,0.0002706752,0.9980013,0.00005790802,0.0000511526,0.001453474],"study_design_scores_gemma":[0.000009649184,0.000167037,0.000939626,0.000006531817,0.000011004,0.00007075634,0.000009679304,0.006064148,0.9904881,0.00003330755,0.002189615,0.00001055611],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.86637,0.00180588,0.1272591,0.0002410407,0.0002069752,0.0002912407,0.0006864542,0.0009564011,0.002182866],"genre_scores_gemma":[0.8946503,0.0006341125,0.1022026,0.0001294923,0.00003042327,0.0004652758,0.0002637067,0.00004911862,0.001574989],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0006236578,"threshold_uncertainty_score":0.002086282,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02238877113718748,"score_gpt":0.2538894040104532,"score_spread":0.2315006328732657,"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."}}