{"id":"W4399512870","doi":"10.1093/restud/rdae064","title":"Job Applications and Labour Market Flows","year":2024,"lang":"en","type":"article","venue":"The Review of Economic Studies","topic":"Labor market dynamics and wage inequality","field":"Economics, Econometrics and Finance","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bank of Canada","funders":"","keywords":"Reservation; Unemployment; Labour economics; Economics; Computer science; 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":[0.0009897971,0.0001202715,0.0002805133,0.001408925,0.0003354745,0.001099693,0.0002900751,0.0005208811,0.005333437],"category_scores_gemma":[0.004250783,0.0001284468,0.0001959232,0.002247984,0.0005416493,0.0008354094,0.0006608914,0.000613917,0.0004869885],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007330365,"about_ca_system_score_gemma":0.0002964423,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003765961,"about_ca_topic_score_gemma":0.003468484,"domain_scores_codex":[0.9994215,0.0002626448,0.00003059773,0.00007895457,0.000100873,0.0001054251],"domain_scores_gemma":[0.9958766,0.00198809,0.001464107,0.00009438564,0.0002440303,0.0003327137],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004768623,0.0004027169,0.6664068,0.000943888,0.000305706,0.0003947028,0.002368703,0.01765488,0.001176084,0.1236046,0.0108159,0.1754491],"study_design_scores_gemma":[0.00002954138,0.0001406073,0.9073028,0.0004812833,0.00006684698,0.0002144913,0.002104542,0.01308205,0.0002700547,0.05269273,0.02357757,0.00003742549],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9395102,0.02929163,0.002859299,0.004893431,0.00009851785,0.0000340035,0.001544735,0.00002263142,0.02174561],"genre_scores_gemma":[0.9915228,0.005633963,0.0001959367,0.0001177224,0.0001383092,0.00001587954,0.000273538,0.000003913578,0.002097939],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005333437,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03874244629464117,"score_gpt":0.2942163637290739,"score_spread":0.2554739174344327,"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."}}