{"id":"W4402423606","doi":"10.24908/iqurcp17849","title":"Microfluidics and Chip Development","year":2024,"lang":"en","type":"article","venue":"Inquiry Queen s Undergraduate Research Conference Proceedings","topic":"3D IC and TSV technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Microfluidics; Chip; Microfluidic chip; Organ-on-a-chip; Nanotechnology; Computer science; Materials science; Telecommunications","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.002951765,0.001438226,0.001743931,0.001727993,0.001099763,0.002620071,0.002723047,0.001668553,0.01843502],"category_scores_gemma":[0.004081209,0.001335129,0.001137772,0.001294668,0.0008926878,0.001542995,0.00253136,0.003017231,0.01519167],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0012679,"about_ca_system_score_gemma":0.002092049,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00101554,"about_ca_topic_score_gemma":0.001269908,"domain_scores_codex":[0.9951238,0.0006380564,0.0003167069,0.0009845595,0.002600891,0.0003358965],"domain_scores_gemma":[0.9985296,0.0003324279,0.0001022316,0.00026916,0.000602435,0.0001641964],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002609741,0.0002693186,0.001258117,0.003585575,0.0001896811,0.0005460276,0.0005438078,0.004369006,0.2484884,0.04934751,0.2042362,0.4869054],"study_design_scores_gemma":[0.00007430703,0.0002553348,0.0006468547,0.0002161611,0.00003672831,0.000564543,0.00004883283,0.005116905,0.09751483,0.003991031,0.8914218,0.0001126885],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01127649,0.04553626,0.8116363,0.006492565,0.01287529,0.005088631,0.007918168,0.02078214,0.07839417],"genre_scores_gemma":[0.05890679,0.03143588,0.7984067,0.006177349,0.00170069,0.01183143,0.008410895,0.00226659,0.08086371],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01843502,"threshold_uncertainty_score":0.06167132,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0787896741680134,"score_gpt":0.3289664441138436,"score_spread":0.2501767699458302,"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."}}