{"id":"W7057308656","doi":"","title":"Islamic banks’ fee income, characteristics and risk: Panel data analysis evidence from Indonesia / Siti Sarah Mat Isa, Masturah Ma’in and Azlina Hanif.","year":2018,"lang":"en","type":"article","venue":"UiTM Institutional Repositories (Universiti Teknologi MARA)","topic":"Superconducting Materials and Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Islam; Panel data; Context (archaeology); Rivalry; Indonesian; Earnings; Net income; Quarter (Canadian coin)","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002018583,0.0002400384,0.0003550857,0.0002723227,0.0004610831,0.0001750488,0.0004142983,0.0001965828,0.00004027066],"category_scores_gemma":[0.0001277345,0.0002584058,0.00003661011,0.0005721533,0.0005210909,0.000927792,0.0004521312,0.0002226359,0.00002019318],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001595336,"about_ca_system_score_gemma":0.00005770906,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00131216,"about_ca_topic_score_gemma":0.00048066,"domain_scores_codex":[0.9986268,0.00006345943,0.0002927261,0.00056043,0.0001925401,0.0002640918],"domain_scores_gemma":[0.9988854,0.0002381685,0.00009905133,0.0006082677,0.0001006311,0.00006847466],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001314681,0.00006642537,0.9187955,0.00011288,0.0008999048,0.0002970112,0.00143841,0.0005967607,0.06571113,0.007735557,0.0002647749,0.003950173],"study_design_scores_gemma":[0.0003109559,0.00004234221,0.9788022,0.0001148777,0.0003717985,0.00007996263,0.000746124,0.016448,0.001494849,0.0004496974,0.0007604947,0.0003787193],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9941397,0.000463915,0.003324512,0.000135939,0.0006278731,0.0001627036,0.000644312,0.0001732227,0.0003277716],"genre_scores_gemma":[0.9956568,0.0008814838,0.002705437,0.00001482119,0.0003469573,0.000007056714,0.0003148642,0.00001442875,0.00005812483],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06421629,"threshold_uncertainty_score":0.9999868,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03255041020976589,"score_gpt":0.2353521347545035,"score_spread":0.2028017245447376,"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."}}