{"id":"W2923282561","doi":"","title":"How Armenian Syrian Millennial Refugees use Social Media to Facilitate Integration into Canadian Society","year":2018,"lang":"en","type":"article","venue":"York University Digital Library (York University)","topic":"Digital Communication and Language","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Armenian; Social media; Refugee; Variety (cybernetics); Meaning (existential); Negotiation; Semiotics; Social exclusion; Psychology; Sociology; Social psychology; Public relations; Political science; Linguistics; Social science; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.00004665603,0.0002896467,0.0002361136,0.0006554447,0.0009011229,0.001968323,0.002486914,0.0001853954,0.00004900338],"category_scores_gemma":[0.00004042325,0.000347845,0.0002460549,0.002123593,0.0003710507,0.01046063,0.001040432,0.0002486522,0.0001997292],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003860981,"about_ca_system_score_gemma":0.0004773559,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001909786,"about_ca_topic_score_gemma":0.01837428,"domain_scores_codex":[0.9983668,0.0001061001,0.0001305442,0.0005908302,0.0002886303,0.0005170619],"domain_scores_gemma":[0.998249,0.0001325885,0.00009636896,0.0006932635,0.00009473231,0.0007340428],"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":[0.0003733413,0.0002901553,0.001690394,0.00003175897,0.0002778617,0.000465044,0.0657772,0.000007811177,0.0002130835,0.5670805,0.2688542,0.0949387],"study_design_scores_gemma":[0.000433475,0.0001062305,0.000822061,0.00002592294,0.00001209855,0.000003393239,0.01125759,0.00009433232,0.0001161803,0.0003820403,0.9863065,0.0004401546],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2890331,0.00006175937,0.03251284,0.02244878,0.0007990194,0.0009740269,0.002359925,0.002507626,0.6493029],"genre_scores_gemma":[0.9346278,0.00000872368,0.009602555,0.00071829,0.0001003358,1.443977e-7,0.0003335202,0.00002061497,0.05458802],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7174523,"threshold_uncertainty_score":0.9998974,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0261413929623473,"score_gpt":0.1769084645589218,"score_spread":0.1507670715965745,"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."}}