{"id":"W4413813897","doi":"10.7554/elife.106557.3.sa3","title":"Author response: Unsupervised pipeline for the identification of cortical excitatory and inhibitory neurons in high-density multielectrode arrays with ground-truth validation","year":2025,"lang":"en","type":"peer-review","venue":"","topic":"Neuroscience and Neural Engineering","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; University of Ottawa","funders":"","keywords":"Excitatory postsynaptic potential; Pipeline (software); Inhibitory postsynaptic potential; Neuroscience; Ground truth; Computer science; Artificial intelligence; 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":[0.001266592,0.0003181462,0.0004935838,0.000297009,0.0002022673,0.0000714592,0.0004044689,0.0001302963,0.000007080233],"category_scores_gemma":[0.005428398,0.0002235591,0.00008767706,0.000769394,0.0002752273,0.0002250041,0.00009569956,0.0005712793,0.00000140582],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006139006,"about_ca_system_score_gemma":0.0002321734,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005101452,"about_ca_topic_score_gemma":0.00002674557,"domain_scores_codex":[0.9970688,0.0004222979,0.0007774279,0.0008570256,0.0005294288,0.0003450116],"domain_scores_gemma":[0.995353,0.003599122,0.0002736963,0.0005595979,0.0001415986,0.0000729126],"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":[0.0005722785,0.0001029175,0.00001253483,0.001451093,0.000004633447,0.00001065699,0.00005370561,0.0001914546,0.9786215,0.0009500919,0.01668086,0.00134824],"study_design_scores_gemma":[0.001293241,0.000398822,0.005488619,0.001341602,0.00027352,0.0000388856,0.00004091022,0.02863573,0.9435604,0.0001377356,0.01816625,0.0006242671],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8622379,0.002042652,0.05998696,0.06167485,0.006258667,0.006916635,0.000473161,0.0003379126,0.00007128267],"genre_scores_gemma":[0.9683769,0.001269155,0.0001376851,0.001946471,0.0001078786,0.000265884,0.00003756396,0.0000490295,0.02780946],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.106139,"threshold_uncertainty_score":0.9116475,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04862595153272862,"score_gpt":0.3157236502716571,"score_spread":0.2670976987389284,"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."}}