{"id":"W4392745865","doi":"10.1109/isscc49657.2024.10454347","title":"ISSCC 2024 Session 33 Overview: Intelligent Neural Interfaces and Sensing Systems","year":2024,"lang":"en","type":"article","venue":"","topic":"Robotics and Automated Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Headset; Session (web analytics); Computer science; Human–computer interaction; Brain–computer interface; Embedded system; Multimedia; Electroencephalography; World Wide Web; Telecommunications; Psychology; Neuroscience","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":[0.000113886,0.0001451861,0.00016629,0.0000983764,0.00003152489,0.0003843747,0.00004673902,0.00006166093,0.00003599438],"category_scores_gemma":[0.000003496704,0.0001077661,0.00003054299,0.000144835,0.00001083677,0.0001128475,0.00004004801,0.0001272899,0.0001050359],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004185559,"about_ca_system_score_gemma":0.000004507968,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007489089,"about_ca_topic_score_gemma":0.000007211366,"domain_scores_codex":[0.9992988,0.00002080109,0.0002395785,0.0001650472,0.0001060274,0.0001697419],"domain_scores_gemma":[0.9997585,0.00004075976,0.000009665202,0.0001162753,0.00001418513,0.0000606371],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00000448531,0.00001576518,0.0001552462,0.007986046,0.0003485745,0.0002917997,0.002644563,0.7054561,0.06535895,0.003547703,0.1016987,0.112492],"study_design_scores_gemma":[0.00002455735,0.00001210254,0.00001760556,0.0008098218,0.00001177405,0.00008506956,0.0004153028,0.9719104,0.003060344,0.00001785844,0.02349758,0.0001376511],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6962031,0.1838794,0.06665532,0.0003239846,0.02535333,0.0006473842,0.00002291057,0.00398388,0.02293065],"genre_scores_gemma":[0.9965253,0.0007772745,0.00012725,0.0000116833,0.0001399837,0.000001571363,0.00000239485,0.00003482672,0.002379694],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3003222,"threshold_uncertainty_score":0.4394572,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02232571697385545,"score_gpt":0.2564629436768789,"score_spread":0.2341372267030234,"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."}}