{"id":"W2349067261","doi":"","title":"High-yielding Multiplication Techniques of CMS Line BJ-1 A with Excellent Quality","year":2011,"lang":"en","type":"article","venue":"Seed","topic":"Distributed and Parallel Computing Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Multiplication (music); Line (geometry); Quality (philosophy); Computer science; Chemistry; Mathematics; Physics; Combinatorics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000401881,0.00009210068,0.0001683638,0.00004871667,0.00004448888,0.00002263203,0.000465158,0.00004796803,0.000002707226],"category_scores_gemma":[0.00001688403,0.00007214006,0.00003475933,0.0002238505,0.00002795732,0.0001053866,0.00009473167,0.00006663967,0.00000979472],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000163013,"about_ca_system_score_gemma":0.00002714093,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007551543,"about_ca_topic_score_gemma":0.00001171156,"domain_scores_codex":[0.9991216,0.00006764061,0.0002697573,0.0002323929,0.0001685678,0.0001400323],"domain_scores_gemma":[0.9991044,0.00004635863,0.0002066305,0.0004801427,0.0001191652,0.00004334077],"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":[0.0005825022,0.003084501,0.1518034,0.001226213,0.0004633199,0.00005144089,0.04376063,0.001861982,0.1876894,0.481661,0.001358623,0.1264571],"study_design_scores_gemma":[0.002144532,0.001516453,0.3848292,0.0007984199,0.00003803962,0.00004187907,0.0003958203,0.04920208,0.5488675,0.008261074,0.002617511,0.001287431],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1789861,0.00002729716,0.8187457,0.00008082377,0.00009016006,0.0001733124,0.000003216776,0.0002522962,0.001641127],"genre_scores_gemma":[0.9059844,0.000002124428,0.09385958,0.00002587598,0.00003685319,0.00001129223,0.00000567055,0.000004592612,0.0000695829],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7269983,"threshold_uncertainty_score":0.2941786,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04655427570716397,"score_gpt":0.2681888664498291,"score_spread":0.2216345907426651,"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."}}