{"id":"W1558034224","doi":"10.1007/978-3-642-14518-6_29","title":"Improved Primality Proving with Eisenstein Pseudocubes","year":2010,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Algorithms and Data Compression","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Primality test; Mathematics; Prime (order theory); Combinatorics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000847446,0.0006729778,0.0006085041,0.0005231163,0.0004458031,0.00103063,0.004226995,0.0004300952,0.00002022973],"category_scores_gemma":[0.00006700556,0.0004987305,0.0001042986,0.0004760736,0.0009252637,0.001257251,0.00260894,0.001587716,0.000020808],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001844089,"about_ca_system_score_gemma":0.0009560122,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008611791,"about_ca_topic_score_gemma":0.0001946891,"domain_scores_codex":[0.9954063,0.00003225459,0.0005186455,0.002131396,0.001097279,0.000814066],"domain_scores_gemma":[0.9961977,0.0002882824,0.0003879814,0.002527777,0.0003327306,0.0002655532],"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":[0.00001913683,0.00005711189,0.00007342185,0.00007488296,0.00001428057,0.0001642335,0.0004341248,0.001325863,0.004594756,0.01013332,0.00001090958,0.983098],"study_design_scores_gemma":[0.0007211306,0.0005870665,0.0003105656,0.0008250072,0.00001749227,0.0003283951,2.11503e-7,0.9165761,0.01810968,0.05620853,0.004596008,0.001719814],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0002894797,0.0001698915,0.9949707,0.0004828151,0.001341221,0.0005807218,0.00001038888,0.000271547,0.001883265],"genre_scores_gemma":[0.04323179,0.0000153605,0.9549891,0.0007374717,0.000592466,0.00001362916,0.000009991299,0.00004709324,0.0003630624],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9813781,"threshold_uncertainty_score":0.9997464,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009704069767134891,"score_gpt":0.2260551091772128,"score_spread":0.2163510394100779,"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."}}