{"id":"W2031883009","doi":"10.1049/iet-cdt.2013.0055","title":"Challenges and advances in Toffoli network optimisation","year":2013,"lang":"en","type":"article","venue":"IET Computers & Digital Techniques","topic":"Quantum Computing Algorithms and Architecture","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Template; Toffoli gate; Computer science; Heuristics; Matching (statistics); Combinatory logic; Computer engineering; Theoretical computer science; Algorithm; Quantum gate; Programming language; Mathematics; Quantum computer; Quantum","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":[0.00271564,0.0007404664,0.001024069,0.0008458706,0.0004522104,0.001942421,0.001586737,0.002124892,0.006411128],"category_scores_gemma":[0.005321814,0.0005283462,0.0007289803,0.001024565,0.001508512,0.004556897,0.001146429,0.002551888,0.00224253],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001705215,"about_ca_system_score_gemma":0.0009513262,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006063097,"about_ca_topic_score_gemma":0.0006285285,"domain_scores_codex":[0.9988585,0.0003212981,0.00005837634,0.0001797156,0.0004850902,0.00009706717],"domain_scores_gemma":[0.9979273,0.001505049,0.00008854915,0.0002064417,0.000219094,0.00005349869],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001269735,0.00007506864,0.000228659,0.001431211,0.00003925744,0.0001073657,0.0001540544,0.1190995,0.004959448,0.5577236,0.007567402,0.3084875],"study_design_scores_gemma":[0.00003258453,0.0001648557,0.0001611381,0.0004000513,0.00002119097,0.0002132875,0.000111278,0.2436514,0.006998531,0.5605897,0.1875967,0.00005940196],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02007851,0.1948724,0.6428251,0.01901975,0.001963888,0.00009374444,0.000274093,0.0008198504,0.1200527],"genre_scores_gemma":[0.3937776,0.2154599,0.3479271,0.003105354,0.002913059,0.0002916413,0.0004985356,0.0006557016,0.03537115],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006411128,"threshold_uncertainty_score":0.02144736,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009906054993092708,"score_gpt":0.2286296666313555,"score_spread":0.2187236116382628,"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."}}