{"id":"W4285306068","doi":"10.1039/d2sd00004k","title":"Uniformity of spheroids-on-a-chip by surface treatment of PDMS microfluidic platforms","year":2022,"lang":"en","type":"article","venue":"Sensors & Diagnostics","topic":"Electrowetting and Microfluidic Technologies","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":"Fonds de Recherche du Québec - Santé; Polytechnique Montréal; Royal Bank of Canada; Natural Sciences and Engineering Research Council of Canada; McGill University","keywords":"Biochip; Spheroid; Microfluidics; Microfluidic chip; Nanotechnology; Materials science; Lab-on-a-chip; Chip; Surface modification; Surface (topology); Chemistry; Computer science; Engineering; Chemical 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009624846,0.0002296007,0.0003492827,0.00007415106,0.00008833435,0.000005038431,0.0002125802,0.00009400427,0.00004438982],"category_scores_gemma":[0.0001002415,0.0002168328,0.0001029799,0.0002808462,0.00009914412,0.00002610954,0.00004950404,0.0001970219,0.000009738214],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000197088,"about_ca_system_score_gemma":0.00003011095,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001085631,"about_ca_topic_score_gemma":0.00000266677,"domain_scores_codex":[0.998898,0.00001674691,0.0003482276,0.000181982,0.0002033888,0.0003516701],"domain_scores_gemma":[0.9990143,0.0004334354,0.0000863203,0.0003901591,0.00003129165,0.00004455719],"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":[0.00004980094,0.0005570466,0.00740434,0.0001034877,0.0002209069,0.00002917425,0.0008084476,0.00788227,0.9019628,0.0007064346,0.07090873,0.009366548],"study_design_scores_gemma":[0.0005369366,0.0009563837,0.0002193801,0.00002116027,0.00004277753,0.00001201158,0.0006044386,0.0001027071,0.9771689,0.0002446108,0.01988677,0.0002039896],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.981073,0.01727564,0.00008188913,0.00006419024,0.0001924264,0.0002150541,0.0003852217,0.0003536025,0.0003589259],"genre_scores_gemma":[0.9855104,0.01389741,0.0002477065,0.000014142,0.00001457773,0.00001212727,0.00005540071,0.00004632118,0.000201875],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07520603,"threshold_uncertainty_score":0.8842186,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007860060390609125,"score_gpt":0.2006064425640761,"score_spread":0.192746382173467,"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."}}