{"id":"W4315631112","doi":"10.1145/3571204","title":"Proto-Quipper with Dynamic Lifting","year":2023,"lang":"en","type":"article","venue":"Proceedings of the ACM on Programming Languages","topic":"Quantum Computing Algorithms and Architecture","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Air Force Office of Scientific Research; Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Syntax; Semantics (computer science); Construct (python library); Operational semantics; Programming language; Dynamic programming; Functional programming; State (computer science); Theoretical computer science; Categorical variable; Algorithm; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":[0.000434438,0.0001831822,0.0001771444,0.0001442489,0.0002304488,0.0002102859,0.002891839,0.00004855873,0.000001027266],"category_scores_gemma":[0.0004955595,0.0001045594,0.00008420042,0.001239075,0.00008636474,0.0001443932,0.001385278,0.0002666025,0.00001190874],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001778511,"about_ca_system_score_gemma":0.00002513381,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001059843,"about_ca_topic_score_gemma":0.000001234321,"domain_scores_codex":[0.9985486,0.000008986756,0.0001848671,0.0003971157,0.0004379471,0.0004224448],"domain_scores_gemma":[0.9989611,0.00009295453,0.0002021472,0.000573877,0.0001150825,0.00005482611],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003654,0.0001559831,0.01016751,0.0004642096,0.00009453162,0.00001942841,0.008871745,0.000595607,0.01106691,0.00954134,0.0008743263,0.9581119],"study_design_scores_gemma":[0.005139808,0.006228494,0.1096237,0.00855653,0.0001915114,0.0007775937,0.01120509,0.5581799,0.2196752,0.04217765,0.03379435,0.004450216],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9916704,0.00006118719,0.0003583493,0.005703749,0.000108011,0.0006822115,0.000001164405,0.0009183759,0.0004965176],"genre_scores_gemma":[0.9003319,0.000002613199,0.09899869,0.0001404729,0.00006578616,0.00008209763,7.224324e-7,0.00002702054,0.0003506904],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9536616,"threshold_uncertainty_score":0.5373805,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008028892670940677,"score_gpt":0.2529775552903836,"score_spread":0.2449486626194429,"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."}}