{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007159205,0.0002361554,0.0002333264,0.0008840805,0.007082848,0.005759119,0.0005325718,0.0006723333,0.022499],"category_scores_gemma":[0.001810246,0.0001806929,0.0001298081,0.002189574,0.005251286,0.001610742,0.003028251,0.00150741,0.001375654],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03645092,"about_ca_system_score_gemma":0.02503385,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8915522,"about_ca_topic_score_gemma":0.9705324,"domain_scores_codex":[0.9988976,0.00008167595,0.00001707912,0.0001316823,0.0002926206,0.0005794463],"domain_scores_gemma":[0.9984385,0.0001514232,0.0001953219,0.00009344336,0.000322728,0.0007985987],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.000165355,0.00005380814,0.1012039,0.0002207674,0.00001948285,0.0008833038,0.2644736,0.0001983362,0.001634631,0.431554,0.1170975,0.08249526],"study_design_scores_gemma":[0.000008464802,0.00002947223,0.2276192,0.0001510537,0.00001636929,0.0001780667,0.06549445,0.0001171569,0.0003667421,0.002612636,0.7033814,0.00002502564],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.4761066,0.002390363,0.0005567883,0.02678685,0.0002029286,0.00005232266,0.001008621,0.00004301627,0.4928525],"genre_scores_gemma":[0.80933,0.0009238796,0.0002427021,0.0008092761,0.00005080514,0.00002040592,0.0002814509,0.00004535809,0.1882961],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1084478,"threshold_uncertainty_score":0.2644712,"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."}}