{"id":"W3118511783","doi":"10.1007/s11135-020-01085-4","title":"Bibliometric maps and co-word analysis of the literature on international cooperation on migration","year":2021,"lang":"en","type":"article","venue":"Quality & Quantity","topic":"Organizational and Employee Performance","field":"Computer Science","cited_by":45,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université TÉLUQ","funders":"","keywords":"Bibliometrics; Immigration; Web of science; Diplomacy; Political science; Refugee; Citation; Field (mathematics); Regional science; Library science; Sociology; Computer science; 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":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.004637055,0.0005592374,0.001029078,0.158908,0.002118588,0.005456927,0.0008670213,0.0005967873,0.01190448],"category_scores_gemma":[0.03739691,0.0002057954,0.00108481,0.2443917,0.001224406,0.004566146,0.002906636,0.0005758906,0.001483217],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002184452,"about_ca_system_score_gemma":0.004307264,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008425477,"about_ca_topic_score_gemma":0.01058814,"domain_scores_codex":[0.9922691,0.002355787,0.0014102,0.0005170261,0.00313662,0.0003113023],"domain_scores_gemma":[0.9354487,0.04757752,0.007414424,0.00172795,0.007197391,0.0006340185],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0009416377,0.0003211918,0.2534702,0.01962186,0.002197961,0.001443407,0.03015306,0.004065668,0.00449798,0.0714202,0.04142756,0.5704393],"study_design_scores_gemma":[0.00008329414,0.0002616143,0.7133127,0.003838694,0.002193884,0.001817056,0.05017062,0.01233554,0.005116284,0.03063706,0.1800246,0.0002085151],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7734152,0.03220455,0.01169792,0.002922169,0.0005794672,0.000343871,0.05055976,0.0008674221,0.1274097],"genre_scores_gemma":[0.9630281,0.01012742,0.009441542,0.00006375353,0.000364323,0.0003576469,0.01187557,0.0001120042,0.00462958],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.841092,"threshold_uncertainty_score":0.03982443,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03402707304082983,"score_gpt":0.3250223004053029,"score_spread":0.2909952273644731,"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."}}