{"id":"W2336367124","doi":"10.2139/ssrn.2666018","title":"The Price Distribution and Technological Shocks in Markets with Endogenous Search Intensity","year":2015,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Housing Market and Economics","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Bank of Canada; Government of Canada","funders":"","keywords":"Economics; Intensity (physics); Distribution (mathematics); Econometrics; Endogeny; Monetary economics; Mathematics; Chemistry; Physics","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":[0.002141382,0.0002697748,0.0009601419,0.001395639,0.0004153134,0.002974129,0.001081093,0.002149358,0.007931497],"category_scores_gemma":[0.02320442,0.0006813155,0.0005815651,0.001238853,0.002341241,0.006327213,0.001556968,0.001788744,0.0005847688],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001002706,"about_ca_system_score_gemma":0.0004292386,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001912688,"about_ca_topic_score_gemma":0.001058217,"domain_scores_codex":[0.9996102,0.0001130225,0.00002584409,0.00006355496,0.00006398676,0.0001233645],"domain_scores_gemma":[0.976724,0.01654952,0.003924284,0.0007914727,0.0007719951,0.001238732],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002008434,0.0006880481,0.08692618,0.0002540898,0.0002849544,0.001944098,0.001228334,0.2288544,0.01395979,0.6337071,0.004109034,0.02603547],"study_design_scores_gemma":[0.0003938237,0.0002427358,0.07003096,0.00003498582,0.00006821598,0.0003848145,0.0007207002,0.6026922,0.001301348,0.3233682,0.0006571986,0.0001048512],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9842201,0.0003267391,0.0110637,0.001444017,0.00001698703,0.00001610366,0.0001742987,0.00004831726,0.002689698],"genre_scores_gemma":[0.9982039,0.0001710942,0.0003284766,0.00003541112,0.00005242745,0.000005552871,0.00006327698,0.000009145468,0.001130698],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007931497,"threshold_uncertainty_score":0.02653348,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02813548375926764,"score_gpt":0.2030519211834401,"score_spread":0.1749164374241725,"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."}}