{"id":"W4206475020","doi":"10.1109/mnano.2021.3126031","title":"Approximate Computing [The Editors’ Desk]","year":2022,"lang":"en","type":"article","venue":"IEEE Nanotechnology Magazine","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Desk; Big data; Computer science; Pleasure; Field (mathematics); Special section; Data science; Library science; Artificial intelligence; Engineering physics; Engineering; Mathematics; Psychology; Data mining","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":[0.002240169,0.002312132,0.002065681,0.003103325,0.001168777,0.004229587,0.002006073,0.003498747,0.03831727],"category_scores_gemma":[0.01269385,0.0007225971,0.001333287,0.002941477,0.0009536575,0.00467342,0.001512115,0.00561839,0.03463615],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002361599,"about_ca_system_score_gemma":0.001676097,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001848885,"about_ca_topic_score_gemma":0.003714592,"domain_scores_codex":[0.9982175,0.0002347486,0.0001662989,0.0003031095,0.0009471048,0.0001311501],"domain_scores_gemma":[0.9932501,0.001625599,0.0002517702,0.0004403342,0.003791546,0.0006406421],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001975099,0.000008522179,0.00002421714,0.0001117566,0.000007001621,0.00002335225,0.000008217966,0.0001320998,0.00005331917,0.001827809,0.9534324,0.04435164],"study_design_scores_gemma":[0.000008755313,0.00001539696,0.0001255855,0.000125935,0.000007937582,0.0001190061,0.00001052497,0.0003757809,0.00007996523,0.0024979,0.9966216,0.00001155214],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.0002333239,0.1098344,0.007053399,0.07602188,0.7720934,0.00004040064,0.0004223403,0.0006457842,0.03365518],"genre_scores_gemma":[0.003825618,0.09296016,0.005725737,0.03266983,0.7368882,0.0000971237,0.0006025896,0.0007663062,0.1264645],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.03831727,"threshold_uncertainty_score":0.128184,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01329624378210584,"score_gpt":0.2438116837819036,"score_spread":0.2305154399997978,"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."}}