{"id":"W4236771096","doi":"10.2139/ssrn.2710353","title":"Correlation Fix","year":2016,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Stochastic Gradient Optimization Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Royal Bank of Canada","funders":"","keywords":"Correlation; Mathematics; Geometry","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":[0.002173982,0.001902096,0.001844137,0.002455079,0.002634037,0.004098395,0.002313871,0.003367489,0.09803028],"category_scores_gemma":[0.01369124,0.0008396663,0.00143878,0.001781195,0.002422342,0.004318358,0.005822264,0.005721446,0.03499895],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00198616,"about_ca_system_score_gemma":0.002655689,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001229882,"about_ca_topic_score_gemma":0.001195914,"domain_scores_codex":[0.9971613,0.0005121459,0.0001022503,0.0009256725,0.0007372493,0.00056146],"domain_scores_gemma":[0.9958819,0.0009303133,0.0002195982,0.001835835,0.0007497249,0.0003826548],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000166617,0.00006613942,0.0003425391,0.0001070831,0.00005418479,0.0001499271,0.00005838793,0.007502259,0.00270193,0.8894849,0.05143389,0.04793204],"study_design_scores_gemma":[0.00008782192,0.0001162206,0.000503158,0.0001276844,0.00007647774,0.0006007557,0.0001179868,0.05156456,0.007277229,0.8464896,0.09295744,0.00008105177],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01239206,0.001319522,0.6950036,0.005292193,0.002776057,0.0003614489,0.00207146,0.004293057,0.2764907],"genre_scores_gemma":[0.4386505,0.002138725,0.1665432,0.007591468,0.001944156,0.001089581,0.003904318,0.005593457,0.3725446],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.09803028,"threshold_uncertainty_score":0.327944,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006442820302268904,"score_gpt":0.2186148889978625,"score_spread":0.2121720686955936,"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."}}