{"id":"W7025529218","doi":"","title":"What influences the direction and magnitude of Asian student mobility? Macro data analysis based on life planning model","year":2022,"lang":"en","type":"article","venue":"Tokyo Tech Research Repository (Tokyo Institute of Technology)","topic":"Global Educational Reforms and Inequalities","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Macro; Destinations; Constraint (computer-aided design); Population; Macro level; Budget constraint; Survey data collection; East Asia","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":[0.002045219,0.000205593,0.0003342955,0.001015862,0.0003973102,0.001485596,0.0004400164,0.0002389022,0.002815598],"category_scores_gemma":[0.006820175,0.0001326105,0.0011071,0.002264921,0.0004371096,0.0009106641,0.0009353613,0.0006501972,0.0003373927],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000789372,"about_ca_system_score_gemma":0.0009073137,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0316813,"about_ca_topic_score_gemma":0.02385079,"domain_scores_codex":[0.9990562,0.000452306,0.00009308869,0.0001526167,0.00008402792,0.0001616599],"domain_scores_gemma":[0.995765,0.002105367,0.0009761134,0.0003503924,0.000424719,0.0003784787],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005361239,0.00002822912,0.9921275,0.0000218784,0.0001134753,0.00006434861,0.0004908762,0.002368711,0.00006066227,0.0007305641,0.0002670479,0.003673085],"study_design_scores_gemma":[0.000007316075,0.0001077358,0.9557285,0.00004359266,0.0001326214,0.00007123045,0.007256711,0.0332462,0.0002444796,0.001378112,0.001754813,0.00002867625],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9941633,0.00006837294,0.0019243,0.0002716373,0.00001056501,0.00002864383,0.0015283,0.00001450856,0.001990305],"genre_scores_gemma":[0.9985306,0.00003734803,0.0004160861,0.00001149029,0.000003252045,0.00001882743,0.0007146514,0.000002952274,0.0002648497],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0316813,"threshold_uncertainty_score":0.06299376,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1223619360212809,"score_gpt":0.446403626103779,"score_spread":0.3240416900824982,"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."}}