{"id":"W2045071098","doi":"10.1111/j.1538-4616.2010.00350.x","title":"Investment Adjustment Costs: An Empirical Assessment","year":2010,"lang":"en","type":"article","venue":"Journal of money credit and banking","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":88,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Economics; Investment (military); Variety (cybernetics); Econometrics; Structural estimation; Shadow price; Shadow (psychology); Asset (computer security); Microeconomics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01581773,0.0007883749,0.0008768067,0.005287,0.0005433591,0.00253869,0.001660984,0.001276112,0.005320387],"category_scores_gemma":[0.1434057,0.0003650859,0.001281182,0.00648854,0.001801657,0.003393292,0.001840782,0.001938579,0.0003736088],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001877623,"about_ca_system_score_gemma":0.0006766394,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003711803,"about_ca_topic_score_gemma":0.003096227,"domain_scores_codex":[0.9917542,0.003529662,0.0007858355,0.0008265291,0.002552131,0.0005515651],"domain_scores_gemma":[0.7039795,0.225838,0.04479161,0.01218321,0.01158745,0.001620161],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001045179,0.0004789178,0.7191507,0.000715228,0.001279239,0.0006602303,0.000464956,0.06309865,0.0005693796,0.06057753,0.005722528,0.1462374],"study_design_scores_gemma":[0.0001889381,0.0008965036,0.7870281,0.0006071866,0.001186829,0.001053804,0.001677177,0.1424687,0.00209136,0.04763659,0.01499825,0.0001666456],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9294829,0.009230493,0.03150678,0.004984071,0.0001467019,0.0002458309,0.001660869,0.0001852021,0.02255711],"genre_scores_gemma":[0.9930571,0.0009713901,0.004129034,0.0001862426,0.0001289753,0.00004451589,0.0007384726,0.00003394254,0.000710344],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01581773,"threshold_uncertainty_score":0.08365315,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06760806260222865,"score_gpt":0.2928160333495559,"score_spread":0.2252079707473272,"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."}}