{"id":"W4312420955","doi":"10.4000/books.aaccademia.11017","title":"KERMIT for Sentiment Analysis in Italian Healthcare Reviews","year":2022,"lang":"en","type":"book-chapter","venue":"Accademia University Press eBooks","topic":"Sentiment Analysis and Opinion Mining","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Institute for Advanced Research","keywords":"Computer science; Syntax; Sentiment analysis; Domain (mathematical analysis); Health care; Natural language processing; Artificial intelligence; Mathematics; Political science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005836771,0.0003615066,0.0009046599,0.0009459531,0.0002744065,0.00007879764,0.001643821,0.0003129126,0.0001329948],"category_scores_gemma":[0.000008076689,0.0004223165,0.0008895758,0.0001289874,0.00004027544,0.0002328304,0.00104372,0.0006095439,0.000008188031],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004442536,"about_ca_system_score_gemma":0.00009328804,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000265316,"about_ca_topic_score_gemma":0.00009043394,"domain_scores_codex":[0.9975958,0.0001254689,0.0005260051,0.0009577645,0.0004189684,0.0003759213],"domain_scores_gemma":[0.9981617,0.000112789,0.0005988566,0.0008968617,0.00007149468,0.0001583247],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002395015,0.00001725278,0.0001972454,0.0001113282,0.001032226,0.00006416919,0.0007589576,0.000123509,0.00000389447,0.9729718,0.009364159,0.01533148],"study_design_scores_gemma":[0.0003669962,0.00003588113,0.00003041285,0.00007971788,0.0006727821,9.796839e-7,0.00003254386,0.002956563,0.00001703823,0.0003979535,0.9949987,0.0004104206],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.00004434751,0.004318066,0.01911644,0.001282095,0.0005947191,0.002433052,0.0001861742,0.0002245726,0.9718006],"genre_scores_gemma":[0.0004693376,0.001152119,0.003324944,0.0003915369,0.00007924672,0.0000109058,0.000167168,0.00002708217,0.9943777],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.9856346,"threshold_uncertainty_score":0.9998229,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06200890571323062,"score_gpt":0.2771779692913871,"score_spread":0.2151690635781565,"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."}}