{"id":"W4407127425","doi":"10.33137/q.i..v44i3.44816","title":"Cinzia Russi. Sicilian Elements in Andrea Camilleri’s Narrative Language: A Linguistic Analysis","year":2025,"lang":"en","type":"article","venue":"Quaderni d italianistica","topic":"Linguistic Studies and Language Acquisition","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Sicilian; Narrative; Art; Linguistics; Literature; Philosophy","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003174814,0.0002622296,0.0004596164,0.0004507946,0.0002412346,0.0001853946,0.0006397332,0.00007385213,0.0005944647],"category_scores_gemma":[0.001104928,0.0002440142,0.0001450242,0.001822874,0.00008206214,0.00007730196,0.0002669098,0.0001871225,0.00009528718],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000174761,"about_ca_system_score_gemma":0.0001022436,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00110839,"about_ca_topic_score_gemma":0.0007501238,"domain_scores_codex":[0.9978856,0.0001146327,0.0005418335,0.0006550219,0.000318408,0.0004844552],"domain_scores_gemma":[0.9987155,0.00021532,0.0001325827,0.0006855083,0.0001540678,0.00009703599],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001812172,0.001545834,0.04960909,0.0004969844,0.004849725,0.005037536,0.2204559,0.0004313395,0.000515617,0.6624843,0.01377227,0.04062015],"study_design_scores_gemma":[0.008412614,0.00136894,0.3156964,0.001326342,0.003824726,0.00004983597,0.1124548,0.4424458,0.001814617,0.03963132,0.0674197,0.005554839],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1517145,0.004962009,0.4452978,0.003333637,0.003563022,0.001588295,0.0001976061,0.0008697999,0.3884733],"genre_scores_gemma":[0.9894382,0.00001339037,0.00689275,0.001039213,0.0001341031,0.00004265772,0.00004251823,0.00001009152,0.00238704],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8377237,"threshold_uncertainty_score":0.9950612,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00873885835159153,"score_gpt":0.2826812981585209,"score_spread":0.2739424398069294,"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."}}