{"id":"W2903688003","doi":"10.1145/3242898","title":"You Cannot Improve What You Do not Measure","year":2018,"lang":"en","type":"article","venue":"ACM Transactions on Reconfigurable Technology and Systems","topic":"Advanced Neural Network Applications","field":"Computer Science","cited_by":69,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Application-specific integrated circuit; Field-programmable gate array; Computer science; Reconfigurability; Convolutional neural network; Digital signal processing; Embedded system; Computer architecture; Ranging; Block (permutation group theory); FPGA prototype; Computer hardware; Computer engineering; 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":[0.0002895825,0.0002485596,0.0003126927,0.0004488229,0.0006969423,0.0002587465,0.001167252,0.0003708452,0.00002483938],"category_scores_gemma":[0.00003635651,0.0002309301,0.00005691976,0.001163325,0.0003206879,0.0008265608,0.00001740762,0.0004817547,0.0001712197],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006392358,"about_ca_system_score_gemma":0.00005174386,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003536026,"about_ca_topic_score_gemma":0.00004068958,"domain_scores_codex":[0.9981325,0.00006261797,0.000394115,0.00077386,0.0001878338,0.0004491238],"domain_scores_gemma":[0.9976057,0.0001385075,0.0001572371,0.001780991,0.0002079585,0.0001095503],"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":[0.00003349419,0.0000989756,0.00003815657,0.00003184858,0.00009409254,0.00000906767,0.0002633746,0.0002965998,0.0171355,0.05636111,0.0003394409,0.9252983],"study_design_scores_gemma":[0.004120325,0.003398682,0.0002855023,0.001160238,0.0002084434,0.002170804,0.005598771,0.05527043,0.515485,0.09719478,0.3117019,0.003405133],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0159279,0.002228038,0.9571178,0.01774076,0.002665934,0.001029049,0.00002434683,0.001502591,0.001763583],"genre_scores_gemma":[0.9926664,0.0004630044,0.004095944,0.0003365195,0.00008865601,0.0004003375,0.000001430819,0.00002158459,0.001926109],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9767385,"threshold_uncertainty_score":0.9417055,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02077787623496065,"score_gpt":0.2497905922941679,"score_spread":0.2290127160592073,"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."}}