{"id":"W7095494109","doi":"","title":"PRELIMINARY AND INCOMPLETE DRAFT","year":2010,"lang":"en","type":"article","venue":"","topic":"Migration and Labor Dynamics","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Immigration; Earnings; Attrition; Longitudinal data; Earnings growth; Longitudinal study","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.008881066,0.0007218063,0.001011801,0.004842031,0.002859872,0.005972775,0.001786713,0.002239414,0.5417847],"category_scores_gemma":[0.0995862,0.0006877453,0.0011626,0.005931075,0.0009227484,0.003429408,0.002614881,0.002946147,0.2994216],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003634439,"about_ca_system_score_gemma":0.008631536,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03110621,"about_ca_topic_score_gemma":0.02919766,"domain_scores_codex":[0.9953498,0.001206649,0.0005364387,0.0005769311,0.001996336,0.0003338186],"domain_scores_gemma":[0.9303148,0.01779185,0.001634217,0.008786925,0.03961566,0.001856462],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000412193,0.00001925679,0.0002764498,0.000168642,0.000009042399,0.00003411765,0.0001432453,0.00007320247,0.00004641886,0.005745197,0.9761929,0.01725028],"study_design_scores_gemma":[0.00002870676,0.00001883682,0.001364648,0.0002280618,0.00001095687,0.00003996692,0.0002470734,0.00008904189,0.00008227375,0.004314349,0.9935616,0.00001440478],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.003647755,0.003730306,0.01699934,0.06838985,0.06563847,0.002639078,0.3033678,0.002848873,0.5327385],"genre_scores_gemma":[0.02605155,0.004913407,0.01480624,0.01504307,0.008660207,0.003081946,0.160239,0.002145899,0.7650588],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.4582153,"threshold_uncertainty_score":0.6535885,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01096705375287339,"score_gpt":0.2867555438025716,"score_spread":0.2757884900496982,"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."}}