{"id":"W2580163882","doi":"10.1112/s0025579317000250","title":"TIGHTER BOUNDS FOR THE DISCREPANCY OF BOXES AND POLYTOPES","year":2017,"lang":"en","type":"preprint","venue":"Mathematika","topic":"Mathematical Approximation and Integration","field":"Mathematics","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Polytope; Combinatorics; Mathematics; Regular polygon; Factorization; Upper and lower bounds; Set (abstract data type); Logarithm; Convex polytope; Discrete mathematics; Point (geometry); Discrete geometry; Space (punctuation); Vector space; Convex set; Algorithm; Convex optimization; Computer science","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":[0.008320022,0.002022146,0.002857546,0.002849226,0.002125745,0.00615763,0.003814816,0.002633551,0.006799344],"category_scores_gemma":[0.05550115,0.001340931,0.002328569,0.00296056,0.006234647,0.013879,0.008841022,0.01068974,0.001063183],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005153048,"about_ca_system_score_gemma":0.001367028,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00137834,"about_ca_topic_score_gemma":0.001126675,"domain_scores_codex":[0.9912436,0.002257169,0.0003876878,0.002240665,0.002828195,0.001042747],"domain_scores_gemma":[0.9422306,0.04245864,0.003412868,0.006930981,0.00257653,0.002390308],"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":[0.000337025,0.0001350091,0.004180688,0.0002764984,0.00008324907,0.0001281845,0.000645551,0.09222204,0.004210242,0.8783838,0.004354197,0.0150436],"study_design_scores_gemma":[0.00004468836,0.0001149449,0.001360842,0.0001270551,0.00004453665,0.0002169964,0.0001849281,0.3115443,0.002959408,0.6769897,0.00635196,0.00006070497],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.190437,0.004436503,0.7650217,0.005595807,0.0004148509,0.0001468909,0.001177742,0.0005609514,0.03220847],"genre_scores_gemma":[0.8239857,0.001800552,0.1626433,0.00117519,0.0007853633,0.0005296405,0.001275394,0.0005683317,0.007236583],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008320022,"threshold_uncertainty_score":0.04400098,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1297259947029574,"score_gpt":0.3925455176225871,"score_spread":0.2628195229196297,"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."}}