{"id":"W171601837","doi":"","title":"Comparing a genetic algorithm penalty function and repair heuristic in the DSP application domain","year":2006,"lang":"en","type":"article","venue":"International conference on Artificial intelligence and applications","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; University of Guelph","funders":"","keywords":"Computer science; Parallel computing; Compiler; Heuristic; Digital signal processing; Bandwidth (computing); High memory; Algorithm; Computer hardware; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003012591,0.001064673,0.001060032,0.002159492,0.0004942797,0.0009574504,0.001270808,0.002122426,0.001081732],"category_scores_gemma":[0.00769832,0.000311717,0.0007318823,0.001411968,0.0008057722,0.0008450557,0.0004757749,0.0008465649,0.0001491576],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001860866,"about_ca_system_score_gemma":0.001689379,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009863026,"about_ca_topic_score_gemma":0.006823794,"domain_scores_codex":[0.9986061,0.0007252825,0.00006197931,0.0001377028,0.0003011218,0.0001677153],"domain_scores_gemma":[0.9936521,0.0052569,0.0002299717,0.0002361252,0.0004910837,0.0001338769],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003432203,0.0001990656,0.001093154,0.00007902774,0.00006744867,0.00004460879,0.00003141633,0.9590039,0.0009665797,0.001905322,0.0003996124,0.0358666],"study_design_scores_gemma":[0.00005257488,0.0002769835,0.0004442816,0.00001046093,0.00003359892,0.00002220664,0.00003227546,0.9969618,0.001089896,0.000672542,0.0003936736,0.000009768598],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.7242305,0.002975565,0.2581581,0.001071634,0.0002305059,0.0002796654,0.0001696128,0.001079758,0.01180466],"genre_scores_gemma":[0.8371094,0.0005763175,0.1594924,0.000241646,0.0000386555,0.0001770697,0.0002413203,0.0001235663,0.001999758],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.009863026,"threshold_uncertainty_score":0.01961124,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05196156630285464,"score_gpt":0.3062921598985927,"score_spread":0.254330593595738,"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."}}