{"id":"W3216810020","doi":"10.1007/978-3-030-81210-2_3","title":"Territorial and Digital Borders and Migrant Vulnerability Under a Pandemic Crisis","year":2021,"lang":"en","type":"book-chapter","venue":"IMISCOE research series","topic":"Migration, Refugees, and Integration","field":"Social Sciences","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Refugee; Forced migration; Population; Political science; Pandemic; Human rights; Displaced person; Vulnerability (computing); Immigration; Development economics; Geography; Economic growth; Sociology; Computer security; Coronavirus disease 2019 (COVID-19); Economics; 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":[0.0005802949,0.0001749963,0.0001207248,0.0006689216,0.001923389,0.003521599,0.0003252327,0.0008784027,0.01066016],"category_scores_gemma":[0.001090762,0.00008262879,0.000128272,0.001020196,0.003354899,0.002869963,0.002339027,0.001338283,0.0006003192],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001503576,"about_ca_system_score_gemma":0.0007970242,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003768275,"about_ca_topic_score_gemma":0.007721299,"domain_scores_codex":[0.9997777,0.0001287776,0.000004325727,0.00002200984,0.00003371427,0.00003341192],"domain_scores_gemma":[0.9993709,0.0004210833,0.00005918349,0.00002364644,0.00004989194,0.00007530865],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.00002953251,0.00006747339,0.008902565,0.0002625974,0.00001124722,0.001073593,0.1586432,0.0007326194,0.0003275547,0.6251373,0.1014552,0.1033571],"study_design_scores_gemma":[0.000004965818,0.00004161787,0.02195922,0.001170366,0.000008309061,0.0009193908,0.2710055,0.0004740148,0.0002078168,0.08825698,0.615933,0.00001900828],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1819032,0.02686371,0.001377897,0.04445143,0.0008593738,0.00003648632,0.0002011175,0.00003602134,0.7442707],"genre_scores_gemma":[0.8590733,0.02492983,0.000868647,0.003201142,0.000408714,0.00007186023,0.0001793186,0.00004037168,0.1112268],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01066016,"threshold_uncertainty_score":0.03566182,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07071307080240054,"score_gpt":0.4006801222334746,"score_spread":0.3299670514310741,"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."}}