{"id":"W2377650939","doi":"","title":"Monetary Policy,Financing Constraints and Corporate Investment","year":2012,"lang":"en","type":"article","venue":"Jingji yu guanli yanjiu","topic":"Environmental and Agricultural Sciences","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Monetary policy; Constraint (computer-aided design); Investment (military); Economics; Monetary economics; Credit channel; Incentive; Finance; China; Investment policy; Quarter (Canadian coin); Inflation targeting; Market economy","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":[0.0008527413,0.0002393553,0.0003253955,0.001463494,0.0003230442,0.001347816,0.0002688217,0.0003927806,0.001861057],"category_scores_gemma":[0.003933596,0.0001540029,0.0002983516,0.001936948,0.0003473458,0.000761529,0.0004482417,0.0003962644,0.0001671447],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0016111,"about_ca_system_score_gemma":0.001080114,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0332206,"about_ca_topic_score_gemma":0.02574938,"domain_scores_codex":[0.9995478,0.00006638538,0.00006984465,0.00006737385,0.0001034255,0.0001451861],"domain_scores_gemma":[0.9961223,0.0006518838,0.002654817,0.00009470509,0.0002178529,0.0002583148],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006335279,0.00002944934,0.9870228,0.00004149459,0.00007474321,0.0002197909,0.000123418,0.003930374,0.0001603331,0.001710218,0.000800361,0.005823773],"study_design_scores_gemma":[0.00001076928,0.00002762731,0.9909871,0.00003204195,0.00005229306,0.00006326217,0.0002462213,0.005631521,0.0002444725,0.0006817796,0.002011179,0.00001186035],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9949765,0.000876085,0.0001663009,0.0003410107,0.000009514084,0.00001290385,0.001255199,0.000005374304,0.002357195],"genre_scores_gemma":[0.9982595,0.0003281298,0.00003683274,0.00002226509,0.00001242746,0.00000747354,0.0009575775,6.986054e-7,0.0003751621],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0332206,"threshold_uncertainty_score":0.06605446,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01650497256015153,"score_gpt":0.2004835770433822,"score_spread":0.1839786044832306,"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."}}