{"id":"W4226382868","doi":"10.22215/etd/2022-14857","title":"Domain-Specific Analog Accelerators for Artificial Intelligent Algorithms Implementation","year":2022,"lang":"en","type":"dissertation","venue":"","topic":"Advanced Memory and Neural Computing","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Implementation; Computer science; Algorithm; Analogue electronics; Artificial neural network; Computer engineering; Artificial intelligence; Electronic circuit; Engineering; Electrical engineering","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","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001121738,0.0002577935,0.000233461,0.0001695711,0.0002411825,0.00005043245,0.0001510081,0.00008812419,0.001514336],"category_scores_gemma":[0.000001556487,0.0002836207,0.0001440785,0.0001886812,0.000005214238,0.0000948848,0.00001516393,0.0002662176,0.00001289055],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001623875,"about_ca_system_score_gemma":0.0000191511,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002791827,"about_ca_topic_score_gemma":0.00008870091,"domain_scores_codex":[0.998799,0.00001557999,0.0004299949,0.0002942422,0.0001711497,0.0002900349],"domain_scores_gemma":[0.9996096,0.00007083186,0.00007927296,0.0001434119,0.00004306369,0.00005379249],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001326557,0.00004034457,0.000006701978,0.0003570176,0.0001480109,0.00001435077,0.002390336,0.02486167,0.06684931,0.01642558,0.006223889,0.8825501],"study_design_scores_gemma":[0.000287231,0.0001555679,0.00007389558,0.00002220155,0.00003893972,0.000003346074,0.01665695,0.00170663,0.525682,0.005917338,0.4486583,0.000797581],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5617576,0.001294106,0.4177015,0.00001855635,0.01060132,0.002177059,0.0002031286,0.001021994,0.005224677],"genre_scores_gemma":[0.8109151,0.0022358,0.09687798,0.0004245075,0.007979,0.003757246,0.06376139,0.001413313,0.01263568],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8817526,"threshold_uncertainty_score":0.9999616,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04021986584260633,"score_gpt":0.3337504679312431,"score_spread":0.2935306020886368,"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."}}