{"id":"W4391902288","doi":"10.5406/23256672.100.2.07","title":"Stiamo (ancora) tutti bene? L'italiano all'estero: dai primi numeri MLA post-pandemia al mercato del lavoro. Il ‘caso’ della GTA di Toronto","year":2023,"lang":"it","type":"article","venue":"Italica","topic":"Second Language Learning and Teaching","field":"Arts and Humanities","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Humanities; Art","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0007829574,0.0009646968,0.0009734081,0.0002019854,0.001430571,0.001335656,0.0009623338,0.0004493095,0.01008423],"category_scores_gemma":[0.000263647,0.0009368063,0.0005532907,0.0001674922,0.0003578097,0.0009602702,0.0004794404,0.001001898,0.003295982],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003503454,"about_ca_system_score_gemma":0.000212581,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02616576,"about_ca_topic_score_gemma":0.01469463,"domain_scores_codex":[0.9947734,0.0004270806,0.001023305,0.001295481,0.0008451697,0.00163558],"domain_scores_gemma":[0.9970691,0.0004306764,0.0004281916,0.001261461,0.0002545625,0.0005560429],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005248945,0.001280281,0.0147871,0.0009518671,0.003475532,0.00194764,0.4003211,0.000359257,0.005609352,0.05297737,0.375999,0.1417666],"study_design_scores_gemma":[0.001250637,0.0006853333,0.006920127,0.0003344252,0.0004576006,0.00008734063,0.04522063,0.001250467,0.0001482761,0.000147999,0.9419461,0.001551012],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9134182,0.0078164,0.00002645093,0.003092157,0.003191972,0.0006053629,0.0008385261,0.001094314,0.06991664],"genre_scores_gemma":[0.899228,0.000278208,0.00008648683,0.004923549,0.001893302,0.00006936579,0.00110583,0.0002675778,0.09214766],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5659472,"threshold_uncertainty_score":0.9998694,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02706086685882269,"score_gpt":0.2739328542217391,"score_spread":0.2468719873629164,"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."}}