{"id":"W2048201255","doi":"10.1142/s0218126605002428","title":"A NOVEL STATE ENCODING ALGORITHM FOR LOW POWER IMPLEMENTATION","year":2005,"lang":"en","type":"article","venue":"Journal of Circuits Systems and Computers","topic":"Error Correcting Code Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Encoding (memory); Computer science; State (computer science); Algorithm; Power (physics); Dissipation; Binary number; Function (biology); Mathematics; Arithmetic; Artificial intelligence","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":[0.0008329985,0.0001265633,0.0002564118,0.0002201908,0.00009762048,0.000295739,0.0004043884,0.00003500605,6.275467e-7],"category_scores_gemma":[0.000009695558,0.0001132948,0.00009104385,0.0001420363,0.00001330469,0.000727579,0.00006331182,0.0001147116,6.254202e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001015867,"about_ca_system_score_gemma":0.00007620878,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002008387,"about_ca_topic_score_gemma":0.000003620565,"domain_scores_codex":[0.9987167,0.00003763758,0.0005694582,0.0001783224,0.0002756434,0.0002222647],"domain_scores_gemma":[0.9987319,0.0001348892,0.0005904228,0.000153287,0.0002851498,0.0001043907],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000002082358,0.0000540304,0.0001323594,0.00004165022,0.00006138176,0.000009023576,0.002760281,0.0006738777,0.005781432,0.002087383,0.001818881,0.9865776],"study_design_scores_gemma":[0.004005447,0.001957772,0.002309858,0.00105636,0.00004596019,0.004179394,0.001072754,0.9559895,0.007723068,0.0008910935,0.01991484,0.0008538917],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01892474,0.0002672306,0.9788952,0.0002118545,0.001342483,0.0002372691,0.000003623113,0.00006469472,0.00005287252],"genre_scores_gemma":[0.8256598,0.00001553766,0.1738621,0.0001601018,0.0002622115,0.000006763038,3.655811e-7,0.00001119025,0.0000219552],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9857237,"threshold_uncertainty_score":0.4620028,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01918611909855993,"score_gpt":0.2836292654400049,"score_spread":0.2644431463414449,"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."}}