{"id":"W2398731595","doi":"10.1007/978-3-642-32512-0_39","title":"A Discrepancy Lower Bound for Information Complexity","year":2012,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Cryptography and Data Security","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Omega; Upper and lower bounds; Communication complexity; Combinatorics; Function (biology); Corollary; Binary logarithm; Mathematics; Discrete mathematics; Computer science; Physics; Mathematical analysis; Quantum mechanics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01061551,0.003903134,0.005654071,0.006351163,0.003564797,0.009220502,0.01003998,0.008541067,0.02028061],"category_scores_gemma":[0.08310652,0.002510562,0.004472608,0.007978248,0.009378137,0.02872274,0.01441276,0.02484186,0.004157535],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01180853,"about_ca_system_score_gemma":0.003884024,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002113678,"about_ca_topic_score_gemma":0.001382553,"domain_scores_codex":[0.985908,0.003381791,0.0004886321,0.002542908,0.005664949,0.002013721],"domain_scores_gemma":[0.8930738,0.08701688,0.002124362,0.009830615,0.004218569,0.00373582],"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":[0.0007021195,0.0002521049,0.00128859,0.0006609574,0.000105395,0.000144848,0.0003707253,0.03308593,0.002416301,0.8968577,0.02669027,0.03742492],"study_design_scores_gemma":[0.0000679904,0.00007323573,0.0004778909,0.0001436869,0.00005882687,0.0001455238,0.00004477549,0.08872776,0.0008013325,0.9026304,0.006776183,0.00005231052],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06780413,0.02078319,0.7133738,0.04760224,0.00331291,0.0002846083,0.003385199,0.001930101,0.1415237],"genre_scores_gemma":[0.7282073,0.01329373,0.1780786,0.01209206,0.009001674,0.001571649,0.003936495,0.002638556,0.05117992],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02028061,"threshold_uncertainty_score":0.08567727,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0225872092154184,"score_gpt":0.2732557279398206,"score_spread":0.2506685187244022,"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."}}