{"id":"W2090072844","doi":"10.1007/s10959-011-0353-8","title":"Strassen-Type Law of the Iterated Logarithm for Self-normalized Sums","year":2011,"lang":"en","type":"article","venue":"Journal of Theoretical Probability","topic":"Probability and Risk Models","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University","funders":"Eli Lilly and Company","keywords":"Strassen algorithm; Law of the iterated logarithm; Mathematics; Iterated logarithm; Logarithm; Type (biology); Independent and identically distributed random variables; Random variable; Sequence (biology); Iterated function; Combinatorics; Natural logarithm; Domain (mathematical analysis); Discrete mathematics; Mathematical analysis; Statistics","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.01374985,0.0001806894,0.0006468663,0.00007147586,0.0001665017,0.00007532418,0.001606031,0.0002025551,0.0005535963],"category_scores_gemma":[0.009049944,0.00008555064,0.0006246099,0.0005291015,0.001964229,0.0003940414,0.0002204407,0.0004232943,0.000007675809],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007339931,"about_ca_system_score_gemma":0.0002914983,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001774856,"about_ca_topic_score_gemma":0.0000168841,"domain_scores_codex":[0.9951917,0.001126326,0.001869982,0.0003210083,0.001171978,0.000319023],"domain_scores_gemma":[0.9934354,0.001905665,0.0009271168,0.0009062556,0.002629306,0.0001962706],"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":[0.001266277,0.0008154279,0.00345199,0.00003736481,0.0000604503,0.000001705129,0.0008332654,0.00009611289,0.0003665784,0.9919133,0.0001839329,0.0009735835],"study_design_scores_gemma":[0.000741813,0.0005693138,0.003919848,0.00002912687,0.000072975,0.00003326488,0.00006102679,0.002381168,0.00908561,0.9824789,0.0005212836,0.000105632],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9667748,0.0001052954,0.02287914,0.001263289,0.001044519,0.0008926654,0.00003646097,0.00002329293,0.006980532],"genre_scores_gemma":[0.9774755,0.000004959316,0.02225637,0.0001608372,0.00006013992,0.000003159812,3.110407e-7,0.000008972981,0.00002977249],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01070067,"threshold_uncertainty_score":0.9992973,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1452062056124414,"score_gpt":0.3561520120349259,"score_spread":0.2109458064224844,"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."}}