{"id":"W4408860552","doi":"10.1109/aiim64537.2024.10934642","title":"Cross-domain Sentiment Classification with Prompt Pre-training and Tuning","year":2024,"lang":"en","type":"article","venue":"","topic":"Sentiment Analysis and Opinion Mining","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Training (meteorology); Domain (mathematical analysis); Artificial intelligence; Sentiment analysis; Machine learning; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.003708361,0.002294498,0.001234466,0.0008241609,0.0005263108,0.001194824,0.002056321,0.001591699,0.002679794],"category_scores_gemma":[0.008385535,0.0006642665,0.001387667,0.0008152573,0.0005917391,0.003143743,0.002262495,0.003458046,0.003139461],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007742794,"about_ca_system_score_gemma":0.001519983,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001951951,"about_ca_topic_score_gemma":0.003059506,"domain_scores_codex":[0.9988015,0.0003427172,0.00009397897,0.0005013663,0.0001333474,0.0001271982],"domain_scores_gemma":[0.9972268,0.00111329,0.0001969155,0.0006800669,0.0005953374,0.0001876395],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0012597,0.001761705,0.01031405,0.0003214387,0.0001814799,0.0002864279,0.00047485,0.1145753,0.05543574,0.002591274,0.01817309,0.794625],"study_design_scores_gemma":[0.00009989116,0.0002830839,0.001938303,0.0000226043,0.00004386972,0.00009011634,0.0001346795,0.973272,0.01670524,0.004102409,0.003272728,0.00003511057],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0999636,0.000600426,0.875663,0.0004115486,0.0002496054,0.0005182634,0.0005369105,0.01958776,0.002468877],"genre_scores_gemma":[0.5614979,0.000363739,0.4269179,0.0008305759,0.0001362613,0.00102646,0.004636457,0.0006549464,0.003935761],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003708361,"threshold_uncertainty_score":0.01961195,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03392989105792804,"score_gpt":0.3042989666662373,"score_spread":0.2703690756083093,"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."}}