{"id":"W4388667248","doi":"10.4204/eptcs.394.16","title":"A Biset-Enriched Categorical Model for Proto-Quipper with Dynamic Lifting","year":2023,"lang":"en","type":"article","venue":"Electronic Proceedings in Theoretical Computer Science","topic":"DNA and Biological Computing","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Categorical variable; Computer science; Machine learning","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001664163,0.0005370426,0.000717867,0.001730576,0.001784466,0.003394021,0.002174128,0.001575956,0.006040762],"category_scores_gemma":[0.002245212,0.0005351382,0.001765399,0.001460136,0.004516745,0.00657123,0.00437221,0.003452042,0.001601914],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002645563,"about_ca_system_score_gemma":0.00180129,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004192958,"about_ca_topic_score_gemma":0.002447833,"domain_scores_codex":[0.9979513,0.0003666504,0.0001501635,0.000456774,0.0006704302,0.0004046909],"domain_scores_gemma":[0.9985263,0.0002910018,0.000121575,0.00036574,0.0004382898,0.0002571305],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00002100294,0.00001227077,0.0001102579,0.00001456953,0.000002781259,0.00006468522,0.0001989455,0.001128261,0.0007344186,0.9959507,0.0002213055,0.001540819],"study_design_scores_gemma":[0.00003302834,0.00005913481,0.0001912277,0.00002069855,0.00001775172,0.0001517008,0.0001610764,0.02601809,0.001907112,0.9546085,0.01679166,0.00003996026],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05169961,0.0002200329,0.9165553,0.0008781748,0.0001701717,0.0001193816,0.0007094656,0.002004916,0.02764299],"genre_scores_gemma":[0.722253,0.0003250463,0.2482023,0.0007593638,0.0002141616,0.0004546657,0.001146792,0.0008417382,0.02580292],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006040762,"threshold_uncertainty_score":0.0202083,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007691420931401275,"score_gpt":0.2635504460324845,"score_spread":0.2558590251010832,"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."}}