{"id":"W2522333996","doi":"10.5539/ijef.v8n10p110","title":"The Impact of Board Size on Firm-Level Capital Investment Efficiency","year":2016,"lang":"en","type":"article","venue":"International Journal of Economics and Finance","topic":"Corporate Finance and Governance","field":"Business, Management and Accounting","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Cash flow; Investment (military); Business; Capital expenditure; Monetary economics; Capital (architecture); Sensitivity (control systems); Capital call; Investment decisions; Information asymmetry; Finance; Economics; Human capital; Economic capital; Market economy","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00223779,0.0001552659,0.0001975104,0.0007044086,0.0002181358,0.001696803,0.0002637878,0.0004025606,0.005527453],"category_scores_gemma":[0.02269989,0.0001110923,0.0001660407,0.000673237,0.0005900208,0.001130433,0.000659333,0.0004392145,0.0004760857],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007235345,"about_ca_system_score_gemma":0.000364,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001863158,"about_ca_topic_score_gemma":0.002567934,"domain_scores_codex":[0.9982855,0.0006688956,0.0001181642,0.0002172423,0.0003158524,0.0003942974],"domain_scores_gemma":[0.9284459,0.03791742,0.02478777,0.002033798,0.002378394,0.004436793],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003789469,0.0001748168,0.9684787,0.00002700409,0.0001506739,0.0002217057,0.0001605814,0.00429778,0.002206496,0.001762059,0.0006427192,0.02149853],"study_design_scores_gemma":[0.00001319662,0.0001830234,0.9959375,0.000008882933,0.00003575561,0.00008693921,0.0002073298,0.001612532,0.0005940565,0.0007934188,0.0005220264,0.000005385428],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9943229,0.0002058478,0.0005221607,0.0002008692,0.000007294548,0.000009820053,0.00009254672,0.000009113577,0.004629433],"genre_scores_gemma":[0.999324,0.00003701986,0.000064622,0.00001399561,0.000007885134,0.000002095079,0.00005253295,0.000001944927,0.0004961034],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005527453,"threshold_uncertainty_score":0.01849121,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01783358869960655,"score_gpt":0.2223991895622614,"score_spread":0.2045656008626548,"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."}}