{"id":"W4221153550","doi":"10.1016/j.cpc.2022.108469","title":"LIBAMI: Implementation of algorithmic Matsubara integration","year":2022,"lang":"en","type":"article","venue":"Computer Physics Communications","topic":"Particle physics theoretical and experimental studies","field":"Physics and Astronomy","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Feynman integral; Sequence (biology); Feynman diagram; Algebra over a field; Computer science; Mathematics; Algorithm; Theoretical computer science; Pure mathematics; Mathematical physics","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":[0.00006860537,0.00008986639,0.0001302857,0.00001909012,0.0004192211,0.0000174735,0.0004285485,0.000004597487,0.0001551493],"category_scores_gemma":[2.223596e-7,0.00009552248,0.00008469533,0.0002150652,0.0001202839,0.0001042167,0.0009169146,0.0001287297,0.00001506243],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003121416,"about_ca_system_score_gemma":0.00001996153,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000153365,"about_ca_topic_score_gemma":4.397947e-7,"domain_scores_codex":[0.9993137,0.0001078075,0.0002132081,0.000114436,0.0001297891,0.0001210216],"domain_scores_gemma":[0.9991978,0.00006169553,0.0001135478,0.0005496001,0.00004888832,0.00002842964],"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":[0.000003131094,0.0003877869,0.002980675,0.000002118879,0.00006459671,3.457658e-8,0.001865258,0.0002731759,0.006161699,0.8274852,0.00034547,0.1604308],"study_design_scores_gemma":[0.001150999,0.0002894124,0.003601771,0.00001424751,0.00008043332,7.864793e-7,0.008022416,0.2864516,0.1000973,0.5975012,0.002317901,0.0004720256],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3016293,0.000173049,0.6885076,0.001067222,0.0002382863,0.000516872,0.0002566286,0.00008467527,0.007526462],"genre_scores_gemma":[0.9814884,0.00000308297,0.0179686,0.0000322628,0.0001008018,0.0001818752,0.0002051564,0.00001018559,0.000009625529],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6798592,"threshold_uncertainty_score":0.3895294,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02517481983354855,"score_gpt":0.3146795909473173,"score_spread":0.2895047711137687,"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."}}