{"id":"W4393407040","doi":"10.1109/hpca57654.2024.00029","title":"Pathfinding Future PIM Architectures by Demystifying a Commercial PIM Technology","year":2024,"lang":"en","type":"article","venue":"","topic":"Electrical Contact Performance and Analysis","field":"Engineering","cited_by":53,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"National Research Foundation of Korea; Ministry of Science and ICT, South Korea; Korea Advanced Institute of Science and Technology; Indian Institute of Technology, Patna","keywords":"Pathfinding; Computer science; Computer architecture; Software engineering; Theoretical computer science","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":[0.0000623477,0.000155361,0.0001774103,0.0003618254,0.00008830166,0.00007512125,0.0001531824,0.0001513556,0.0001274396],"category_scores_gemma":[0.000007067948,0.0001247543,0.00008727848,0.0009238503,0.00001585257,0.00006429866,0.00002560408,0.0004835444,0.00008921298],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005395824,"about_ca_system_score_gemma":0.00001016198,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001068366,"about_ca_topic_score_gemma":0.0000319043,"domain_scores_codex":[0.999231,0.000006928984,0.000161207,0.0001673465,0.0001068741,0.0003266902],"domain_scores_gemma":[0.9997737,0.00003565801,0.000007292312,0.0001234791,0.000009473363,0.00005041028],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000006185409,0.00001944787,0.003074259,0.0002617691,0.0003144997,0.00005594554,0.0003710671,0.001365697,0.06984805,0.003350759,0.03645571,0.8848766],"study_design_scores_gemma":[0.0004886653,0.0002167506,0.001130269,0.0002528095,0.0002999234,0.0000894464,0.000493807,0.4113558,0.1029865,0.002842096,0.4783246,0.001519302],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9399685,0.01561742,0.02882349,0.002685485,0.0004896505,0.0001185699,0.00001216183,0.003031494,0.009253267],"genre_scores_gemma":[0.998559,0.0002516924,0.000318703,0.0001671667,0.0003294991,0.00001522525,0.00001028591,0.00002914325,0.0003192609],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8833573,"threshold_uncertainty_score":0.5087332,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003144031904512885,"score_gpt":0.2062436334779114,"score_spread":0.2030996015733985,"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."}}