{"id":"W2970390435","doi":"10.1016/j.ssresearch.2019.102344","title":"Disentangling the role of income in the academic achievement of migrant children","year":2019,"lang":"en","type":"article","venue":"Social Science Research","topic":"Early Childhood Education and Development","field":"Social Sciences","cited_by":14,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Saskatchewan; McMaster University; University of British Columbia","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Numeracy; Literacy; Poverty; Psychology; Logistic regression; Population; Demography; Developmental psychology; Demographic economics; Sociology; Medicine; Economic growth; Economics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0141378,0.00004644504,0.00009506884,0.0001774948,0.0009140853,0.0000518396,0.001474361,0.00004965645,0.00006149984],"category_scores_gemma":[0.0003979762,0.00002762379,0.00004118713,0.00266025,0.001873008,0.0001609402,0.0001666319,0.0004157936,0.00002297515],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001694193,"about_ca_system_score_gemma":0.001565309,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003541643,"about_ca_topic_score_gemma":0.0004691589,"domain_scores_codex":[0.9962932,0.000545472,0.0002234298,0.0001720857,0.002294375,0.0004713794],"domain_scores_gemma":[0.999187,0.0003317328,0.00007703324,0.000158116,0.0001917666,0.00005438598],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000003601975,0.00003955724,0.747143,0.000002048702,0.000002218803,3.769388e-8,0.1927715,9.837121e-7,0.0004931788,0.05359638,0.0000288644,0.005918569],"study_design_scores_gemma":[0.00008372421,0.0000190065,0.880004,0.00001835956,9.908474e-7,7.991081e-8,0.1100373,0.000005630642,0.0004560691,0.007908266,0.001426637,0.0000398576],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9712457,0.0001746852,2.881916e-7,0.005980678,0.00007991463,0.0005607595,0.00000188602,0.00000412883,0.02195194],"genre_scores_gemma":[0.9996034,0.0000776825,0.00001474092,0.00005759998,0.0001117068,0.00001328528,5.798156e-7,0.000002456897,0.0001185482],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.132861,"threshold_uncertainty_score":0.7030498,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0404886540619018,"score_gpt":0.4268966633454568,"score_spread":0.386408009283555,"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."}}