{"id":"W4401115349","doi":"10.1371/journal.pdig.0000545","title":"Evaluating automatic annotation of lexicon-based models for stance detection of M-pox tweets from May 1st to Sep 5th, 2022","year":2024,"lang":"en","type":"article","venue":"PLOS Digital Health","topic":"Sentiment Analysis and Opinion Mining","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada); Regional Municipality of Niagara; Brock University; Response Biomedical (Canada); University of Toronto; York University","funders":"International Development Research Centre; Styrelsen för Internationellt Utvecklingssamarbete","keywords":"Lexicon; Annotation; Computer science; Artificial intelligence; Natural language processing; Labeled data; Transformer; Social media; Machine learning; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002456377,0.001385229,0.0005829828,0.001897368,0.0005561782,0.001246455,0.001114267,0.001086537,0.001553255],"category_scores_gemma":[0.006974814,0.0003609913,0.0007872799,0.0007354551,0.0004339803,0.001581468,0.0008319573,0.001021753,0.002026986],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001679993,"about_ca_system_score_gemma":0.001240548,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02334254,"about_ca_topic_score_gemma":0.04385509,"domain_scores_codex":[0.9987255,0.0004845032,0.0000996708,0.0004328718,0.0001548443,0.0001025373],"domain_scores_gemma":[0.9969317,0.001914146,0.000184295,0.0003067224,0.0005470906,0.0001160471],"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":[0.003534436,0.001974612,0.1309567,0.001463465,0.000800029,0.0008593812,0.001616638,0.2210025,0.03198283,0.003491139,0.05524079,0.5470774],"study_design_scores_gemma":[0.00007399244,0.0002640422,0.01238644,0.00006558806,0.00008276682,0.00009840743,0.0003589232,0.9728889,0.007940767,0.001122554,0.004678098,0.00003955129],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8982317,0.001929317,0.06091061,0.001052643,0.0004904957,0.0004345764,0.010672,0.01471349,0.01156501],"genre_scores_gemma":[0.922107,0.0003440081,0.04507736,0.0002949102,0.00008615456,0.0002583623,0.02745207,0.0003391858,0.004040867],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02334254,"threshold_uncertainty_score":0.04641336,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1097679616781885,"score_gpt":0.38802400234012,"score_spread":0.2782560406619314,"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."}}