{"id":"W4399583372","doi":"10.1002/wom3.38","title":"Gender and migration: Trends, gaps and urgent action","year":2024,"lang":"en","type":"article","venue":"World Migration Report","topic":"Migration and Labor Dynamics","field":"Social Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wilfrid Laurier University; Balsillie School of International Affairs","funders":"","keywords":"Action (physics); Economic geography; Political science; Geography","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":[0.005381318,0.0002916463,0.000891173,0.002484073,0.002131553,0.005003274,0.001120096,0.002360562,0.01658437],"category_scores_gemma":[0.006781066,0.0002917461,0.0005266881,0.006193375,0.00238556,0.008013871,0.002422543,0.002640394,0.001297394],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003699976,"about_ca_system_score_gemma":0.01003386,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02259188,"about_ca_topic_score_gemma":0.04505351,"domain_scores_codex":[0.9980358,0.0007052181,0.0001697055,0.0002448775,0.000287521,0.0005568532],"domain_scores_gemma":[0.9943789,0.002410972,0.0009589056,0.0001370419,0.0008591399,0.001255086],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0003850333,0.000250209,0.1557686,0.006440888,0.0001175003,0.00068662,0.02706547,0.0002330901,0.000267635,0.05285891,0.1883846,0.5675414],"study_design_scores_gemma":[0.00002466999,0.0002396491,0.3046376,0.01541629,0.0000983021,0.001623551,0.2607439,0.0004662093,0.00009852022,0.02726439,0.3892827,0.0001041583],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.06419898,0.3895309,0.0003883721,0.5270942,0.00483633,0.00004157579,0.002141825,0.00006234638,0.01170544],"genre_scores_gemma":[0.5331457,0.4181782,0.001196407,0.0339604,0.005908576,0.0001547287,0.002123996,0.00004734024,0.005284529],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02259188,"threshold_uncertainty_score":0.05548024,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03754077551738538,"score_gpt":0.3399533394808485,"score_spread":0.3024125639634632,"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."}}