{"id":"W4392739381","doi":"10.1109/isscc49657.2024.10454460","title":"33.5 Closed-Loop 100-Channel Highly-Scalable Retinal Implant with 1.02μW Analog ED-Based Adaptive-Threshold Spike Detection and Poisson-Coded Temporally Distributed Optogenetic Stimulation","year":2024,"lang":"en","type":"article","venue":"","topic":"Neuroscience and Neural Engineering","field":"Neuroscience","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Optogenetics; Scalability; Computer science; Spike (software development); Retinal implant; Closed loop; Channel (broadcasting); Retinal; Electronic engineering; Neuroscience; Engineering; Telecommunications; 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001843748,0.00035079,0.0002542769,0.0002774184,0.000282329,0.0003020268,0.0002070085,0.00009759558,0.00002318731],"category_scores_gemma":[0.00006840604,0.0002741478,0.00006524373,0.001013277,0.0001523335,0.0004691322,0.0000679875,0.0003067418,0.0000230801],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007335031,"about_ca_system_score_gemma":0.00008000023,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007479617,"about_ca_topic_score_gemma":0.00003419427,"domain_scores_codex":[0.9975935,0.00005846829,0.0003266872,0.0009698673,0.0005017124,0.0005497607],"domain_scores_gemma":[0.9991947,0.0001849917,0.00007186916,0.0002793263,0.00004658681,0.0002225479],"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":[0.0002693886,0.00004741645,0.0001747288,0.00006097043,0.000004275352,0.0002859755,0.0000165845,0.02786393,0.970118,0.0003823616,0.0001178326,0.0006585109],"study_design_scores_gemma":[0.0003911112,0.0007073845,0.001379895,0.00007341426,0.00002320803,0.0001646604,0.000008887982,0.4582939,0.5384411,0.00007033612,0.0001885264,0.0002575171],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9494557,0.0000686322,0.04830382,0.000351076,0.0004339894,0.0005040771,0.00009883896,0.0005804071,0.0002034293],"genre_scores_gemma":[0.9989829,0.00003364749,0.0002483737,0.0002680331,0.00007350381,0.00003354446,0.00001596285,0.00004681845,0.0002971939],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4316769,"threshold_uncertainty_score":0.9999711,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02502685811964372,"score_gpt":0.2481681937629593,"score_spread":0.2231413356433155,"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."}}