{"id":"W2142158920","doi":"","title":"The Impact of Leased and Rented Assets on Industry Productivity Measurement","year":2014,"lang":"en","type":"article","venue":"","topic":"Financial Reporting and Valuation Research","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Lease; Finance; Business; Renting; Asset (computer security); Balance sheet; Productivity; Fixed asset; Capital (architecture); Collateral; Economics; Production (economics); Microeconomics; Engineering","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":[0.034687,0.0007684958,0.0009369552,0.002910437,0.001138991,0.004355507,0.002356751,0.0009639307,0.003590193],"category_scores_gemma":[0.2247885,0.0004086601,0.001361112,0.009057601,0.002182889,0.002846328,0.003001474,0.001606918,0.001287845],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005381542,"about_ca_system_score_gemma":0.003445948,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1234359,"about_ca_topic_score_gemma":0.06334963,"domain_scores_codex":[0.9174553,0.03732776,0.004142237,0.008500041,0.02901247,0.003562206],"domain_scores_gemma":[0.5929397,0.3105458,0.04393129,0.02573694,0.02492992,0.001916382],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008384764,0.000299996,0.9272517,0.0002299417,0.0007186723,0.0002342073,0.001060401,0.01519406,0.0007236585,0.003614504,0.002353209,0.04748112],"study_design_scores_gemma":[0.00003814029,0.0008560318,0.9693468,0.0001177233,0.0002479966,0.0001172443,0.001435815,0.01567477,0.004357289,0.001547592,0.006191616,0.0000690056],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9299955,0.002144647,0.01669966,0.001642133,0.0002770016,0.0002859494,0.009178721,0.0003746763,0.03940169],"genre_scores_gemma":[0.9914293,0.0002668501,0.003391298,0.0001718794,0.00005092714,0.00008733915,0.002810073,0.00005048694,0.00174182],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1234359,"threshold_uncertainty_score":0.2454349,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0911804682299689,"score_gpt":0.3386251325646704,"score_spread":0.2474446643347015,"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."}}