{"id":"W7095359817","doi":"","title":"Earnings dynamics in Canada: an econometric analysis","year":2002,"lang":"en","type":"article","venue":"","topic":"Labor market dynamics and wage inequality","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Earnings; Distribution (mathematics); Hazard; Econometric analysis; Earnings response coefficient; Duration (music); Conditional probability; Situated","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":[0.001144501,0.0003548255,0.0005086782,0.00321625,0.001462662,0.00153718,0.001106759,0.000465534,0.005129157],"category_scores_gemma":[0.004913916,0.0003083951,0.0007735205,0.005927784,0.0006288973,0.000390114,0.0007449257,0.0008370365,0.0005802242],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02676341,"about_ca_system_score_gemma":0.01774094,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9929537,"about_ca_topic_score_gemma":0.9861616,"domain_scores_codex":[0.9993232,0.00008148229,0.00002507103,0.00008119837,0.0002217008,0.0002673386],"domain_scores_gemma":[0.9976748,0.0007984301,0.00023863,0.000102473,0.0009668636,0.0002188892],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003806281,0.0003300622,0.8347836,0.0001208531,0.0002069872,0.0007177307,0.001199776,0.09021991,0.0003515783,0.01157745,0.01316919,0.04694235],"study_design_scores_gemma":[0.0000509004,0.00006141336,0.782402,0.00004700905,0.00009769388,0.0001046015,0.002302672,0.2032458,0.0001971162,0.001162542,0.01026023,0.00006803385],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9817922,0.0005681637,0.001357491,0.0007039799,0.00001138072,0.00009917341,0.00897339,0.0001001225,0.006394195],"genre_scores_gemma":[0.9804074,0.0008118477,0.001466153,0.00007789824,0.000016245,0.00004814496,0.009995396,0.00002064324,0.007156336],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02676341,"threshold_uncertainty_score":0.1941831,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02370297495038399,"score_gpt":0.1916685490678413,"score_spread":0.1679655741174573,"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."}}