{"id":"W1964495605","doi":"10.1016/j.aca.2008.03.047","title":"A cell-microelectronic sensing technique for profiling cytotoxicity of chemicals","year":2008,"lang":"en","type":"article","venue":"Analytica Chimica Acta","topic":"Neuroscience and Neural Engineering","field":"Neuroscience","cited_by":87,"is_retracted":false,"has_abstract":false,"ca_institutions":"Alberta Health Services; University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Water Network","keywords":"Chemistry; Microelectronics; Profiling (computer programming); Cytotoxicity; Nanotechnology; Chromatography; 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":[],"consensus_categories":[],"category_scores_codex":[0.0001287507,0.0001905401,0.0002992307,0.0001499285,0.0001687629,0.00001548771,0.0003422047,0.00007617374,0.000006101006],"category_scores_gemma":[0.0005361211,0.0001776297,0.0001688393,0.0005457608,0.0001931453,0.0001630161,0.00007742825,0.0002358244,0.000003290059],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004368986,"about_ca_system_score_gemma":0.00009179312,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001225536,"about_ca_topic_score_gemma":1.644784e-7,"domain_scores_codex":[0.9984022,0.00002888971,0.0003327216,0.0005022382,0.0002205197,0.0005134009],"domain_scores_gemma":[0.999079,0.0003191818,0.0001319875,0.0003324435,0.00003847064,0.000098927],"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":[0.00002200362,0.00005173508,0.00001177821,0.00003887387,0.000001725092,0.000005086299,0.00002554626,0.000004441563,0.9994845,0.0002321985,0.0001109861,0.00001112063],"study_design_scores_gemma":[0.0001911548,0.0001151979,0.00001586008,0.00002181406,0.0000145523,0.0001323475,0.000003377587,0.007787892,0.9913062,0.0001297473,0.0001001437,0.0001817463],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9975278,0.000004418147,0.0008630194,0.0001984362,0.00004528109,0.0005930462,0.00001430241,0.0001015837,0.0006521023],"genre_scores_gemma":[0.9968326,0.00008329437,0.002573356,0.0002987334,0.00004383392,0.00001741423,0.000001371703,0.00003046346,0.0001189063],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008178338,"threshold_uncertainty_score":0.7243529,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03119009001464932,"score_gpt":0.2640615397276581,"score_spread":0.2328714497130087,"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."}}