{"id":"W4376139577","doi":"10.1080/08865655.2023.2202210","title":"The “Who is Who” of Migration Information Campaigns on Social Media","year":2023,"lang":"en","type":"article","venue":"Journal of Borderlands Studies","topic":"Social Media and Politics","field":"Social Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Danmarks Frie Forskningsfond","keywords":"Social media; Corporate governance; Construct (python library); Public relations; Political science; Information sharing; Social network analysis; Social network (sociolinguistics); Sociology; Business; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007770633,0.00006186523,0.0002099368,0.0001011428,0.0007653859,0.00003906927,0.0001293295,0.00006188485,0.000005223358],"category_scores_gemma":[0.002469583,0.00003988662,0.0001012293,0.0003657318,0.0002614021,0.0002057929,0.00001785592,0.0001229997,0.000009542789],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005862965,"about_ca_system_score_gemma":0.0001637802,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000620459,"about_ca_topic_score_gemma":0.0007272367,"domain_scores_codex":[0.9986944,0.0001192584,0.0003687597,0.00002963629,0.0006036467,0.0001842877],"domain_scores_gemma":[0.9976097,0.001328315,0.0004093754,0.00004007736,0.0005712368,0.00004125615],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00003663876,0.00001168782,0.008311384,0.00001493079,0.0001425406,0.000001207525,0.8170303,0.000002825916,0.000007527486,0.007806302,0.1574121,0.009222667],"study_design_scores_gemma":[0.000417879,0.0001338262,0.03414653,0.00006441236,0.00005895573,4.48206e-7,0.7125884,0.000008896526,0.0001599109,0.008424961,0.2439115,0.00008417456],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9726896,0.0003800672,0.000005417277,0.02262217,0.001588393,0.00007836931,0.00001623617,0.00001427717,0.002605451],"genre_scores_gemma":[0.9913568,0.006812868,0.000008030777,0.000238726,0.00136734,0.00000316292,0.000001518607,0.000003697398,0.0002078458],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1044418,"threshold_uncertainty_score":0.5886807,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06093916974923149,"score_gpt":0.3706614177790431,"score_spread":0.3097222480298116,"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."}}