{"id":"W2905923430","doi":"10.3968/10395","title":"Financial Deepening and the Performance of Manufacturing Firms in Nigeria","year":2018,"lang":"en","type":"article","venue":"Canadian social science","topic":"Working Capital and Financial Performance","field":"Business, Management and Accounting","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Distributed lag; Production (economics); Index (typography); Industrial production index; Manufacturing sector; Economics; Business; Chow test; Capitalization; Value (mathematics); Market capitalization; Finance; Financial services; Financial system; Macroeconomics; Econometrics; Statistics; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006201621,0.00007144624,0.0001108516,0.0001743572,0.0007553363,0.0001148828,0.0002982242,0.00003520554,0.00002319617],"category_scores_gemma":[0.00007199373,0.00005546915,0.00001862304,0.0006336471,0.001415025,0.0006525455,0.0000855827,0.00009011614,0.0000225161],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005615835,"about_ca_system_score_gemma":0.000120625,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.009743324,"about_ca_topic_score_gemma":0.03737362,"domain_scores_codex":[0.9992126,0.000002784275,0.000133793,0.000153754,0.0001522659,0.0003447789],"domain_scores_gemma":[0.9997694,0.000009435396,0.00007585249,0.00007177857,0.00005786213,0.00001560393],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001549444,0.00001529436,0.7367436,0.0001351041,0.000003425534,0.000009836867,0.005281984,0.000007033873,0.000451905,0.1354245,0.0007233162,0.1210491],"study_design_scores_gemma":[0.0006802474,0.0000146036,0.9745329,0.00007106576,0.000004849202,0.000001324402,0.000475082,0.001491796,0.001001281,0.002398374,0.01908334,0.0002451143],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9595619,0.000023459,0.000002728023,0.0002727688,0.0003095318,0.00009032509,6.178317e-7,0.000007381617,0.03973126],"genre_scores_gemma":[0.9982747,0.000003909944,0.00001277411,0.0007947401,0.0008629739,0.000004367409,3.891557e-7,0.000004026387,0.00004206561],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2377893,"threshold_uncertainty_score":0.9968509,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00658612455953063,"score_gpt":0.187517791062894,"score_spread":0.1809316665033634,"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."}}