{"id":"W2797100274","doi":"","title":"Dynamic Refugee Matching","year":2018,"lang":"en","type":"article","venue":"Papyrus : Institutional Repository (Université de Montréal)","topic":"Migration, Refugees, and Integration","field":"Social Sciences","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Refugee; Matching (statistics); Computer science; Locality; Mechanism (biology); Asylum seeker; Bounded function; Computer security; Law; Political science; Mathematics; Statistics","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":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0003136453,0.0001333962,0.000124435,0.0001342272,0.01095934,0.00007490948,0.0002639656,0.0001520333,0.000167813],"category_scores_gemma":[0.00007093421,0.0001412302,0.0001038723,0.0002641778,0.0004942036,0.0005772726,0.00005836224,0.0001352029,0.0001791208],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003253569,"about_ca_system_score_gemma":0.0008852031,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.0488387,"about_ca_topic_score_gemma":0.1556087,"domain_scores_codex":[0.9986205,0.0001436861,0.0001838792,0.0002793613,0.0004760739,0.0002965461],"domain_scores_gemma":[0.9992015,0.00004370426,0.0001228385,0.0001994284,0.0002470262,0.0001854724],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002381485,0.000145875,0.008606642,0.00001731094,0.000107487,0.0001671864,0.3258069,0.0001596596,0.0212513,0.628369,0.004375084,0.01075543],"study_design_scores_gemma":[0.0005318723,0.0001196895,0.02148224,0.00006795091,0.00006482216,0.00009397735,0.05469225,0.001411285,0.002770057,0.006856302,0.9114875,0.0004220335],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8450128,0.001177598,0.002434475,0.0006789317,0.0007611041,0.0001716837,0.000008634333,0.0001744843,0.1495802],"genre_scores_gemma":[0.9501194,0.0001691583,0.001031806,0.0001703972,0.0002990729,0.000005406403,0.00002047565,0.000008895407,0.04817538],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9071124,"threshold_uncertainty_score":0.9903283,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005717670972505174,"score_gpt":0.2081785861720511,"score_spread":0.2024609151995459,"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."}}