{"id":"W1978061565","doi":"10.1109/icecs.2006.379840","title":"Implantable Smart Medical Microsystems: Limits and Challenges","year":2006,"lang":"en","type":"article","venue":"","topic":"Neuroscience and Neural Engineering","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"Canada Research Chairs","keywords":"Microsystem; Computer science; Reliability (semiconductor); Power management; Electrical engineering; Medical device; Power (physics); Voltage; Embedded system; Electronic engineering; Engineering; Biomedical engineering; Materials science; Nanotechnology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001171294,0.0001042399,0.0001185552,0.00005573016,0.00009967567,0.0000502576,0.0001674377,0.00004946885,0.00002871013],"category_scores_gemma":[0.0000873485,0.00008114635,0.00001987937,0.000115655,0.000071672,0.0001832937,0.00005334775,0.00009536254,0.00004727963],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006373044,"about_ca_system_score_gemma":0.00001465549,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000047455,"about_ca_topic_score_gemma":0.00003147293,"domain_scores_codex":[0.9989097,0.00002693889,0.0001422595,0.0003435997,0.0002865938,0.0002909421],"domain_scores_gemma":[0.999586,0.0001573052,0.00002034338,0.0001228212,0.000005491146,0.0001080223],"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":[0.000002874118,0.00002323835,0.0001145182,0.00003451852,2.478232e-7,0.00006379517,0.00001249753,0.000002579174,0.9866579,0.01033327,0.0009327077,0.001821886],"study_design_scores_gemma":[0.0002031209,0.00004808286,0.000888197,0.00002311658,0.000001703576,0.0009207767,0.00001385922,0.001234221,0.9332814,0.0001212227,0.06311397,0.0001503033],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9533632,0.0007935803,0.0000562224,0.002595311,0.0005004539,0.0001293952,0.0000039281,0.0002629806,0.04229488],"genre_scores_gemma":[0.9964438,0.001353883,0.0000199548,0.0006188194,0.0001122436,0.000006234027,2.157219e-7,0.00001061361,0.001434242],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06218126,"threshold_uncertainty_score":0.3309052,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04658885066009532,"score_gpt":0.2432700451589666,"score_spread":0.1966811944988712,"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."}}