{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003252253,0.00006565845,0.00008626546,0.00006290877,0.0001656139,0.00009868238,0.00006927613,0.00004487868,0.00003201454],"category_scores_gemma":[0.004496925,0.00003647698,0.00003716348,0.0001882452,0.00004256048,0.0001210716,0.00004345697,0.0001562623,0.00001310163],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002351954,"about_ca_system_score_gemma":0.00004660212,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001210843,"about_ca_topic_score_gemma":0.00007161237,"domain_scores_codex":[0.9990573,0.0000263193,0.0001631757,0.0001369798,0.0004781909,0.0001380252],"domain_scores_gemma":[0.9991907,0.00004966347,0.0001633306,0.000188124,0.0003995292,0.000008677318],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002024951,0.0003111801,0.7581832,0.00009410699,0.00006429807,9.301376e-7,0.00001476886,0.0002584605,0.008408734,0.0129744,0.02904409,0.1904433],"study_design_scores_gemma":[0.0002503643,0.00004445858,0.9888523,0.00002889943,0.000007302959,2.48021e-7,0.00001365618,0.004469125,0.0007758152,0.001191915,0.004302981,0.00006291429],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9786177,0.000008390337,0.0000809649,0.001146461,0.00005904857,0.0001587047,1.595994e-7,0.00002408411,0.01990453],"genre_scores_gemma":[0.9993293,7.768933e-7,0.000005665298,0.00003615838,0.0002067234,0.000007074965,0.000001102142,0.000005236769,0.0004079754],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2306691,"threshold_uncertainty_score":0.5383564,"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."}}