{"id":"W2158258198","doi":"10.1021/bp025733x","title":"On-Line Monitoring of Cell Growth and Cytotoxicity Using Electric Cell-Substrate Impedance Sensing (ECIS)","year":2003,"lang":"en","type":"article","venue":"Biotechnology Progress","topic":"Microfluidic and Bio-sensing Technologies","field":"Engineering","cited_by":205,"is_retracted":false,"has_abstract":true,"ca_institutions":"Biotechnology Research Institute; National Research Council Canada","funders":"National Research Council Canada","keywords":"Cytotoxicity; Cell culture; Biophysics; Cell growth; Chemistry; Cell; Cell biology; Materials science; Biology; Biochemistry; In vitro","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":[0.0001508978,0.0002904637,0.0003477429,0.0003513918,0.0001065097,0.00002181071,0.0001892303,0.0006916189,9.568619e-7],"category_scores_gemma":[0.00006275768,0.0002814353,0.00004950622,0.0006233429,0.0003231399,0.00005519007,0.00006270115,0.0004745703,0.0000026297],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005339014,"about_ca_system_score_gemma":0.00002467246,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004822655,"about_ca_topic_score_gemma":2.707957e-7,"domain_scores_codex":[0.9986835,0.00002820487,0.0003240638,0.000350466,0.0001233667,0.0004903876],"domain_scores_gemma":[0.9993786,0.00005314672,0.0001137169,0.0003682363,0.00004457754,0.00004172626],"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":[0.00001016073,0.00003972167,0.001393464,0.0001370675,0.00001684536,0.00003009726,0.00001902541,0.00007096998,0.9940302,0.0006754581,0.00001581976,0.003561173],"study_design_scores_gemma":[0.000318727,0.00015903,0.0001110489,0.00007965037,0.0000237004,0.0000641359,0.00008746784,0.004241975,0.9939865,0.0006278626,0.00002731638,0.0002725266],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9855236,0.00778561,0.005048083,0.0000388584,0.0002027836,0.0002073682,0.000004120025,0.001058623,0.0001309836],"genre_scores_gemma":[0.9716434,0.001866838,0.0264158,0.000004332607,0.00002170553,0.000001952914,6.646286e-7,0.00004094425,0.000004336199],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02136771,"threshold_uncertainty_score":0.9999638,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01731345541232951,"score_gpt":0.2313909903555599,"score_spread":0.2140775349432304,"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."}}