{"id":"W2135722987","doi":"10.3390/s150510465","title":"Towards a Dynamic Clamp for Neurochemical Modalities","year":2015,"lang":"en","type":"article","venue":"Sensors","topic":"Neuroscience and Neural Engineering","field":"Neuroscience","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Defense Advanced Research Projects Agency; Washington State University","keywords":"Microfluidics; Nanosensor; Neurochemical; Artificial neural network; Neural cell; Computer science; Biological system; Nanotechnology; Lab-on-a-chip; Interface (matter); Microfluidic chip; Artificial intelligence; Materials science; Chemistry; Neuroscience; Cell; Biology","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":[0.00007810513,0.000129623,0.0001258969,0.00006571369,0.00006312307,0.00004720123,0.0002269042,0.00004099271,0.000003239268],"category_scores_gemma":[0.001049845,0.0001160842,0.00006774703,0.0002011913,0.00009932667,0.0001262962,0.00005200866,0.0001134858,0.00002801141],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003120437,"about_ca_system_score_gemma":0.00004035023,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003979196,"about_ca_topic_score_gemma":6.494718e-7,"domain_scores_codex":[0.9988837,0.00002704035,0.0001366628,0.0003592919,0.0002447297,0.0003485908],"domain_scores_gemma":[0.9994736,0.0001170675,0.00002856524,0.000189619,0.0000248609,0.0001662934],"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":[0.00003211141,0.00001772386,0.000004928918,0.00001302454,4.627433e-7,0.00002151983,0.0002001985,0.001166872,0.9954306,0.002262137,0.0002640852,0.0005863415],"study_design_scores_gemma":[0.0003611109,0.0001247315,0.00003308977,0.000006062325,0.000004054608,0.00007756142,0.00008206804,0.110367,0.8784848,0.001942425,0.008329622,0.0001875069],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9961965,0.000008578198,0.0002887065,0.0008015779,0.000650908,0.0001874214,0.00001578991,0.0002016435,0.001648884],"genre_scores_gemma":[0.9971462,0.000008746093,0.0002314168,0.0008646132,0.00006434073,0.00001912442,8.888519e-7,0.00002380014,0.001640817],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1169458,"threshold_uncertainty_score":0.4733776,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0788742668681447,"score_gpt":0.3085898785976752,"score_spread":0.2297156117295305,"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."}}