{"id":"W2902131086","doi":"10.1016/j.jeca.2018.e00111","title":"Is the investment-cash flow sensitivity divergent when information is asymmetrically distributed?","year":2018,"lang":"en","type":"article","venue":"The Journal of Economic Asymmetries","topic":"Corporate Finance and Governance","field":"Business, Management and Accounting","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Cash flow; Investment (military); Metric (unit); Sensitivity (control systems); Divergence (linguistics); Economics; Constraint (computer-aided design); Flow (mathematics); Econometrics; Measure (data warehouse); Microeconomics; Finance; Mathematics; Computer science","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":[0.004986685,0.0003753092,0.001184598,0.00112492,0.0003997329,0.004442741,0.001195173,0.002307807,0.007339313],"category_scores_gemma":[0.05949366,0.0006971057,0.000512121,0.000679396,0.00205343,0.009147632,0.001721264,0.0025255,0.000640763],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008796381,"about_ca_system_score_gemma":0.0005417774,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008069501,"about_ca_topic_score_gemma":0.0003717593,"domain_scores_codex":[0.9985327,0.0003802639,0.00008761371,0.0003326059,0.0003631353,0.0003037203],"domain_scores_gemma":[0.9577539,0.03174139,0.004699505,0.002997951,0.001447661,0.001359634],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.004517408,0.0007190928,0.1071508,0.0008259884,0.0006692507,0.002836782,0.002900737,0.07397268,0.05207656,0.5962439,0.00636429,0.1517225],"study_design_scores_gemma":[0.0001758066,0.0002270106,0.103963,0.0001219399,0.0002373182,0.0009631841,0.001226176,0.07486989,0.005433805,0.811274,0.001371715,0.0001362188],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9537115,0.0006713423,0.01844605,0.003546419,0.0001048546,0.00002488989,0.0002616849,0.0000965724,0.02313664],"genre_scores_gemma":[0.9986454,0.0001386114,0.0004599431,0.0001427323,0.00004829593,0.000004066132,0.0000411916,0.00001222254,0.0005075475],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007339313,"threshold_uncertainty_score":0.02637243,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01956519267584404,"score_gpt":0.2095224203300163,"score_spread":0.1899572276541722,"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."}}