{"id":"W3207721929","doi":"10.1002/pra2.568","title":"Where Did They Come From? On Global Mobility of Chinese Returnees","year":2021,"lang":"en","type":"article","venue":"Proceedings of the Association for Information Science and Technology","topic":"Migration and Labor Dynamics","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Web of science; Regional science; Economic geography; Political science; Geography; MEDLINE; Law","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":[0.001209417,0.0001399133,0.0002035189,0.002702447,0.00109449,0.001246602,0.0003844797,0.0002901498,0.004461462],"category_scores_gemma":[0.004122009,0.00006120517,0.0002193826,0.004164567,0.0007172679,0.001094343,0.001493936,0.000340591,0.0004713165],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008866594,"about_ca_system_score_gemma":0.000973598,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03555507,"about_ca_topic_score_gemma":0.03908533,"domain_scores_codex":[0.9992719,0.0001822994,0.00005713086,0.00008879455,0.000127035,0.0002728593],"domain_scores_gemma":[0.9968265,0.000592891,0.001392227,0.0001717862,0.0004687073,0.0005478954],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007682623,0.00002168596,0.9654621,0.00005352553,0.00003639356,0.0003132885,0.01663703,0.0000946076,0.0003659488,0.0008993497,0.0008367182,0.01520257],"study_design_scores_gemma":[0.000003310995,0.00003616708,0.9461759,0.00004771165,0.00002395192,0.0001370139,0.04931732,0.000222366,0.0001512095,0.0002642857,0.00360796,0.00001285193],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977621,0.0002137491,0.00007480071,0.0003269065,0.00000766386,0.000005179972,0.0002361073,0.000002292451,0.001371284],"genre_scores_gemma":[0.9990024,0.000181908,0.00004342115,0.0000380292,0.00001017558,0.000007197543,0.0001537173,0.000001478967,0.0005617831],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03555507,"threshold_uncertainty_score":0.07069623,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006061087167264088,"score_gpt":0.2721858295290089,"score_spread":0.2661247423617448,"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."}}