{"id":"W2070041664","doi":"10.1016/j.bios.2014.02.026","title":"Tumor cell characterization and classification based on cellular specific membrane capacitance and cytoplasm conductivity","year":2014,"lang":"en","type":"article","venue":"Biosensors and Bioelectronics","topic":"Microfluidic and Bio-sensing Technologies","field":"Engineering","cited_by":94,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Cytoplasm; Membrane; Cell; Flow cytometry; Chemistry; Microfluidics; Cell membrane; Cell biology; Biophysics; Molecular biology; Materials science; Biology; Nanotechnology; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001242836,0.0001708831,0.0001611268,0.00008118765,0.00009399817,0.00005306002,0.0000401931,0.0001239118,0.00000229491],"category_scores_gemma":[0.00001211212,0.0001504604,0.00001535724,0.0001006827,0.0001368171,0.00005311479,0.000008604608,0.0001503001,0.000003186449],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003167339,"about_ca_system_score_gemma":0.000007412163,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001797416,"about_ca_topic_score_gemma":0.00000163739,"domain_scores_codex":[0.9992979,0.00002641581,0.0001261326,0.0002568038,0.00007344467,0.0002192578],"domain_scores_gemma":[0.99969,0.0000375292,0.00004163853,0.0001667327,0.00002006337,0.00004406696],"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":[0.0000130275,0.00001450617,0.0001591724,0.00005708196,0.000002863838,9.914671e-7,0.0000171584,0.000003129193,0.9923809,0.0007691882,0.00009101464,0.006490954],"study_design_scores_gemma":[0.000281831,0.0001598168,0.002139925,0.00001980614,0.000009760831,0.000008038394,0.00002300946,0.04520515,0.9382486,0.00004970458,0.01364542,0.0002089683],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9945654,0.000707412,0.003898998,0.0002428532,0.00007742675,0.000125254,0.00001647646,0.0002201732,0.0001460514],"genre_scores_gemma":[0.9971182,0.002255226,0.0004453062,0.00005097454,0.00004098702,0.000002143434,0.00002625295,0.00001867804,0.0000422108],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05413234,"threshold_uncertainty_score":0.6135598,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009628163281696921,"score_gpt":0.1674960599871568,"score_spread":0.1578678967054599,"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."}}