{"id":"W2107222991","doi":"10.1017/s089006040800019x","title":"Evolving blackbox quantum algorithms using genetic programming","year":2008,"lang":"en","type":"article","venue":"Artificial intelligence for engineering design analysis and manufacturing","topic":"Quantum Computing Algorithms and Architecture","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Computer science; Quantum sort; Quantum computer; Quantum algorithm; Quantum; Genetic programming; Theoretical computer science; Algorithm; Quantum complexity theory; Quantum network; Quantum mechanics; Artificial intelligence; Physics","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":[0.0004311859,0.0003261327,0.0004266679,0.0006103104,0.0005107555,0.0003123012,0.0004965991,0.00009007257,0.000004468065],"category_scores_gemma":[0.000067674,0.0003140015,0.0002746696,0.0006974811,0.00006184098,0.0002658865,0.0001598133,0.0001977092,0.000003155853],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004705597,"about_ca_system_score_gemma":0.0000372297,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009898795,"about_ca_topic_score_gemma":0.000002845018,"domain_scores_codex":[0.9978316,0.0000394547,0.0005369618,0.0006918612,0.0002646541,0.0006354456],"domain_scores_gemma":[0.998901,0.0002916568,0.0001341359,0.0004126896,0.00007533778,0.0001851805],"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":[0.000003835902,0.00002874445,0.00003184999,0.00002541104,0.0002298541,0.00002848699,0.0006768118,0.8691579,0.001263618,0.001123247,0.000002392369,0.1274279],"study_design_scores_gemma":[0.00002761156,0.00008307492,0.0003451516,0.00002507448,0.0001370563,0.00005460022,0.00003177567,0.9453921,0.05178086,0.00162796,0.0001134016,0.0003813106],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1265801,0.000299329,0.8723502,0.00004269656,0.0002077093,0.0002670299,0.000001451684,0.0002502579,0.000001229223],"genre_scores_gemma":[0.5359038,0.00002181377,0.4639168,0.00001256718,0.0001087496,0.00001331087,0.000001416521,0.00001716675,0.00000443991],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.4093237,"threshold_uncertainty_score":0.9999312,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03989968752805621,"score_gpt":0.2562014924601071,"score_spread":0.2163018049320509,"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."}}