{"id":"W4408077220","doi":"10.1101/2025.02.25.640239","title":"A novel in vitro 3D cancer model based on modular tissue engineering approach","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"3D Printing in Biomedical Research","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Saskatchewan Cancer Agency; University of Saskatchewan; Saskatchewan Health Authority","funders":"","keywords":"Modular design; In vitro; Tissue engineering; Cancer; Computer science; Biomedical engineering; Computational biology; Engineering; Biology; Medicine; Internal medicine; Programming language; Biochemistry","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0001992914,0.0006323713,0.0002617909,0.0004567223,0.0002114484,0.0005447634,0.0004547565,0.0008024979,0.001297129],"category_scores_gemma":[0.00011259,0.0003617902,0.0005692309,0.0002746984,0.0002949059,0.0003091092,0.0004261739,0.0006402407,0.0005806919],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003729007,"about_ca_system_score_gemma":0.000443184,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001594012,"about_ca_topic_score_gemma":0.00166058,"domain_scores_codex":[0.9998587,0.00001745875,0.00001044516,0.0000414033,0.00005478773,0.00001709431],"domain_scores_gemma":[0.9998939,0.00002688622,0.00002056494,0.00002843507,0.0000105109,0.00001965504],"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":[0.00005008722,0.00003767374,0.0002589932,0.00008732558,0.00001391874,0.0003798176,0.00005175321,0.0279386,0.9640241,0.00236121,0.0003198404,0.004476646],"study_design_scores_gemma":[0.00004287005,0.0002579851,0.001738628,0.00003067576,0.00005658781,0.001377499,0.00003132775,0.1694773,0.7987853,0.001161395,0.026977,0.00006345058],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3673934,0.002467068,0.607729,0.0004866713,0.0004440199,0.00038061,0.002910016,0.002293926,0.01589534],"genre_scores_gemma":[0.7274459,0.001544285,0.2595702,0.0001653717,0.00004229131,0.0005040732,0.001410299,0.0001932936,0.009124232],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001594012,"threshold_uncertainty_score":0.004339278,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01633645726811717,"score_gpt":0.2429358583573034,"score_spread":0.2265994010891863,"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."}}