{"id":"W4223548340","doi":"10.3390/mi13040587","title":"Uniform Tumor Spheroids on Surface-Optimized Microfluidic Biochips for Reproducible Drug Screening and Personalized Medicine","year":2022,"lang":"en","type":"article","venue":"Micromachines","topic":"3D Printing in Biomedical Research","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Sciences and Engineering Research Council of Canada; McGill University; McGill University Health Centre; Polytechnique Montréal","funders":"Polytechnique Montréal; Royal Bank of Canada; McGill University","keywords":"Spheroid; Biochip; Biomedical engineering; Cell culture; In vivo; Materials science; Lung cancer; Microfluidics; 3D cell culture; Chemistry; Nanotechnology; Cancer research; Biology; Medicine; Pathology; Biotechnology","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001882671,0.0002796048,0.0004070099,0.0001798559,0.0004568897,0.00004053717,0.0003820993,0.00004006778,0.0004985437],"category_scores_gemma":[0.0004140163,0.0002464896,0.00009144888,0.0004220411,0.0002401577,0.00005232638,0.0002489417,0.0004782044,0.000008449502],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009608785,"about_ca_system_score_gemma":0.00003129116,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001980539,"about_ca_topic_score_gemma":0.000003403842,"domain_scores_codex":[0.998005,0.0001105756,0.0003633655,0.0005745179,0.0004265006,0.0005199965],"domain_scores_gemma":[0.9987746,0.0004935155,0.0000523516,0.0004568568,0.00004972897,0.0001729136],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005621229,0.00008384423,0.001167979,0.0004626551,0.0001831512,0.00003107919,0.001507981,0.002367285,0.8925407,0.000233882,0.09294207,0.007917274],"study_design_scores_gemma":[0.0219565,0.001391856,0.002797197,0.000581651,0.0001959267,0.0004002081,0.003067605,0.1583853,0.2703253,0.002352812,0.5363231,0.00222256],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9808176,0.01131112,0.002914586,0.002477119,0.0004641446,0.0006762497,0.00009817127,0.0004361546,0.0008048076],"genre_scores_gemma":[0.95757,0.0005213692,0.03617343,0.0005978748,0.0004839539,0.0001981631,0.0002171321,0.0002348939,0.004003198],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6222154,"threshold_uncertainty_score":0.9999987,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02314483107127627,"score_gpt":0.2728676293966067,"score_spread":0.2497227983253305,"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."}}