{"id":"W2095686887","doi":"10.1109/iembs.2007.4353873","title":"A Microsystem Integration Platform Dedicated to Build Multi-Chip-Neural Interfaces","year":2007,"lang":"en","type":"article","venue":"Conference proceedings","topic":"Neuroscience and Neural Engineering","field":"Neuroscience","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Interfacing; Microsystem; Computer science; Microprobe; Chip; Interface (matter); Stacking; Computer hardware; SIGNAL (programming language); Electrode; Signal processing; Embedded system; Electronic engineering; Materials science; Engineering; Nanotechnology; Digital signal processing","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":[0.0003414749,0.000642536,0.0004377138,0.0004742271,0.0003222973,0.0005326137,0.001165706,0.0006970569,0.005850493],"category_scores_gemma":[0.0003223489,0.000336968,0.0003995571,0.0002693096,0.0002210595,0.0005777145,0.0009103123,0.0008757969,0.001965425],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003204727,"about_ca_system_score_gemma":0.0005356323,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002280992,"about_ca_topic_score_gemma":0.0004068881,"domain_scores_codex":[0.9996489,0.00002701167,0.00001544687,0.00007828305,0.0001879534,0.00004240828],"domain_scores_gemma":[0.9998393,0.00002656693,0.00001924369,0.00004008438,0.000047421,0.00002733358],"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":[0.00009618276,0.0001035125,0.0006975734,0.0005311882,0.00008208781,0.0003077806,0.00007726483,0.003461662,0.8603781,0.00713425,0.004018942,0.1231114],"study_design_scores_gemma":[0.0000492532,0.001448326,0.005629814,0.00006011824,0.0001168529,0.001798022,0.0000503092,0.03234051,0.8220404,0.001836092,0.1345703,0.00006000924],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06870695,0.003032755,0.9093786,0.0003094625,0.0007968165,0.0005404993,0.0007763138,0.00660341,0.009855266],"genre_scores_gemma":[0.2854845,0.001619181,0.6962982,0.0002886779,0.0001539526,0.001101414,0.00169091,0.0003620139,0.01300119],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005850493,"threshold_uncertainty_score":0.01957184,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07719834732626907,"score_gpt":0.3037330721213655,"score_spread":0.2265347247950964,"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."}}