{"id":"W4411064840","doi":"10.1155/hbe2/9829676","title":"Corrigendum to “Consumer Savings and Digital Remittance in Open Banking: Insights From Bibliometric and Geospatial Econometric Analysis”","year":2025,"lang":"en","type":"erratum","venue":"Human Behavior and Emerging Technologies","topic":"FinTech, Crowdfunding, Digital Finance","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Geospatial analysis; Remittance; Econometric analysis; Computer science; Economics; Econometrics; Geography; Cartography; Economic growth","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":[0.002517865,0.001421826,0.001507942,0.005505398,0.003902061,0.004550481,0.002353222,0.004464032,0.1046697],"category_scores_gemma":[0.06804711,0.0008226427,0.001511745,0.006017724,0.001914609,0.002917852,0.002285432,0.006073316,0.06149665],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006866106,"about_ca_system_score_gemma":0.004704497,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09159914,"about_ca_topic_score_gemma":0.1023197,"domain_scores_codex":[0.9949937,0.0007728585,0.0007612184,0.0005340852,0.002651662,0.0002864187],"domain_scores_gemma":[0.9408957,0.01055209,0.001489025,0.002356435,0.04391253,0.0007942319],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000004893971,0.00000432815,0.00008610663,0.00004702706,0.00000418671,0.00006531614,0.00002921645,0.00003073414,0.00001445269,0.0007616844,0.9957312,0.003220953],"study_design_scores_gemma":[0.0000136997,0.00001203911,0.001720734,0.0003337045,0.0000317752,0.0002217506,0.0002361205,0.000468722,0.0003019296,0.002214361,0.994399,0.00004604322],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"other","genre_scores_codex":[0.0004696709,0.002248534,0.001765768,0.13324,0.8360467,0.0000620461,0.004822067,0.0006487296,0.02069658],"genre_scores_gemma":[0.02594736,0.0140398,0.006193053,0.1122239,0.1882136,0.0003589789,0.01114507,0.002244338,0.639634],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.1046697,"threshold_uncertainty_score":0.3501551,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03472949948371647,"score_gpt":0.2767009980335954,"score_spread":0.241971498549879,"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."}}