{"id":"W7028518337","doi":"","title":"FINANCIAL TECHNOLOGY AND LIQUIDITY IN THE NIGERIAN BANKING SECTOR","year":2019,"lang":"en","type":"article","venue":"Covenant University Repository (Covenant University)","topic":"Economic Growth and Development","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Market liquidity; Payment; Order (exchange); Loan; Payment system; Quarter (Canadian coin); Clearing; Distributed lag","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005168316,0.0001484045,0.0001482204,0.001388616,0.001136694,0.003039222,0.0001195449,0.0006413302,0.003431658],"category_scores_gemma":[0.002252165,0.000143898,0.0001515722,0.001653939,0.0007111975,0.001222519,0.0008562339,0.000577772,0.000260836],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001213109,"about_ca_system_score_gemma":0.001420112,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008054422,"about_ca_topic_score_gemma":0.01297801,"domain_scores_codex":[0.999667,0.0001181056,0.00003620277,0.00002194693,0.0000623786,0.00009434232],"domain_scores_gemma":[0.9980161,0.0006558485,0.0009917686,0.0000177926,0.0001562073,0.0001622574],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002545261,0.0003843013,0.952003,0.0003004429,0.00002683483,0.002737316,0.008007651,0.000855945,0.0008815674,0.007650673,0.001223618,0.02567404],"study_design_scores_gemma":[0.00002402122,0.0002450469,0.952691,0.001030524,0.0000499213,0.001462129,0.03145682,0.001682577,0.0004883644,0.003408606,0.007425291,0.00003571337],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9875858,0.003588906,0.00004979374,0.001105402,0.00001240375,0.00001206035,0.00006871609,0.000001614507,0.00757531],"genre_scores_gemma":[0.9975784,0.001636077,0.00003558749,0.00006508282,0.00001012099,0.000003677591,0.00002231858,4.468033e-7,0.0006481842],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008054422,"threshold_uncertainty_score":0.01601511,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004947230190521246,"score_gpt":0.1408693483174115,"score_spread":0.1359221181268903,"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."}}