{"id":"W2104193487","doi":"10.1109/tc.2009.173","title":"Algorithmic Aspects of Hardware/Software Partitioning: 1D Search Algorithms","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Computers","topic":"Embedded Systems Design Techniques","field":"Computer Science","cited_by":58,"is_retracted":false,"has_abstract":true,"ca_institutions":"Nortel (Canada)","funders":"","keywords":"Algorithm; Computer science; Knapsack problem; Heuristic; Software; Combinatorics; Theoretical computer science; Mathematics; Artificial intelligence; Programming language","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"],"consensus_categories":[],"category_scores_codex":[0.0003703973,0.0002753487,0.0003683768,0.0004704974,0.0002094563,0.0001399987,0.001088911,0.0001376314,0.00001783724],"category_scores_gemma":[0.000004266273,0.0002895473,0.0002239627,0.0008251172,0.00007934032,0.0005557096,0.000005472777,0.0003774355,0.0000467212],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000154281,"about_ca_system_score_gemma":0.0001691676,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005454565,"about_ca_topic_score_gemma":0.000004029444,"domain_scores_codex":[0.9976293,0.0001826604,0.0004963772,0.0006039384,0.0006421968,0.000445481],"domain_scores_gemma":[0.9983299,0.0002119916,0.0001281448,0.0009286634,0.0002188514,0.0001824573],"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":[0.00002787156,0.0008721768,0.00001340363,0.00006255433,0.0001422328,0.000138228,0.001687578,0.05288728,0.004639076,0.01000733,0.002903145,0.9266191],"study_design_scores_gemma":[0.001155098,0.002273122,0.0003838942,0.0005873772,0.00003592018,0.0002444225,0.00004636123,0.413239,0.5736904,0.006519727,0.00087807,0.0009465761],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0006089894,0.00004283023,0.9957002,0.000435496,0.0009233996,0.0004294899,0.00001231728,0.001135585,0.000711715],"genre_scores_gemma":[0.6844225,0.00001406379,0.3151174,0.000260689,0.00006068894,0.00002312017,0.000001549023,0.00001551035,0.0000844315],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9256725,"threshold_uncertainty_score":0.9999557,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02679554778028945,"score_gpt":0.2722061593095307,"score_spread":0.2454106115292413,"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."}}