{"id":"W2543247044","doi":"10.1109/icm.2013.6734985","title":"Multi-modal neural microprobe integrating silicon microelectrodes and polymeric microchannels","year":2013,"lang":"en","type":"article","venue":"","topic":"Neuroscience and Neural Engineering","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Microelectrode; Microprobe; Interfacing; Microchannel; Materials science; Electrode; Multielectrode array; Neural activity; Biomedical engineering; Silicon; Brain implant; Nanotechnology; Optoelectronics; Computer science; Neuroscience; Chemistry; Engineering; Computer hardware; Mineralogy","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002441927,0.0003004399,0.0001589071,0.0002317359,0.0001038826,0.000190547,0.0003464217,0.0003733458,0.0006095936],"category_scores_gemma":[0.0002909889,0.0001831981,0.0001560636,0.0001023622,0.0002243227,0.0004130839,0.0002341923,0.0002262814,0.000203305],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001832841,"about_ca_system_score_gemma":0.0001478076,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002625483,"about_ca_topic_score_gemma":0.0007876307,"domain_scores_codex":[0.9998791,0.0000140087,0.00001109766,0.00004369947,0.00003346729,0.00001854498],"domain_scores_gemma":[0.9997818,0.00007955416,0.00005717484,0.00002150798,0.0000382634,0.0000217058],"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":[0.00001699301,0.000004599298,0.00005203804,0.00002826088,0.000002027347,0.00001925112,0.000004537365,0.00005647916,0.9985414,0.00007522462,0.00001283206,0.001186389],"study_design_scores_gemma":[0.000005552652,0.0002057262,0.001227454,0.000004411842,0.000007720534,0.0001794754,0.000008082637,0.001913967,0.9951239,0.00005209997,0.001265398,0.000006202169],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8819683,0.003033079,0.1120644,0.000173223,0.00007942381,0.000126434,0.0002493457,0.0004772824,0.001828662],"genre_scores_gemma":[0.868509,0.001153273,0.1268221,0.0001153922,0.00003366542,0.0001309795,0.0001532815,0.00003811788,0.00304427],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0006095936,"threshold_uncertainty_score":0.002039313,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01980368973597995,"score_gpt":0.2403127510751474,"score_spread":0.2205090613391674,"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."}}