{"id":"W6966929376","doi":"10.48448/a5f2-gx95","title":"uChecker: Masked Pretrained Language Models as Unsupervised Chinese Spelling Checkers","year":2022,"lang":"en","type":"other","venue":"Underline Science Inc.","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Spelling; Language model; Masking (illustration); Task (project management); Word (group theory); Feature (linguistics); Error detection and correction; Labeled data","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":[0.0009159427,0.001644691,0.0007928046,0.000807686,0.0004100468,0.0008387088,0.002231374,0.0009738365,0.002816063],"category_scores_gemma":[0.002965316,0.0005951214,0.001166712,0.0005449402,0.000632133,0.001418435,0.001164577,0.00184628,0.002177158],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007486805,"about_ca_system_score_gemma":0.001732221,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01273568,"about_ca_topic_score_gemma":0.01819913,"domain_scores_codex":[0.9994231,0.0001361776,0.00003360801,0.0002471408,0.00008574596,0.00007412433],"domain_scores_gemma":[0.9988779,0.0004375709,0.0001249037,0.0002621747,0.0002222022,0.00007516319],"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":[0.001057313,0.0004054033,0.004598021,0.000266232,0.0003118513,0.0004910384,0.0003153833,0.3336541,0.0313812,0.00721579,0.01833364,0.6019701],"study_design_scores_gemma":[0.00001712389,0.00007431202,0.0004134795,0.00001265577,0.00002251943,0.00004535188,0.00001503798,0.9912946,0.00463423,0.002391343,0.001060676,0.0000187109],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1037675,0.001059466,0.8635756,0.0007579087,0.000356975,0.0002693722,0.0022893,0.02401403,0.003909799],"genre_scores_gemma":[0.7362372,0.0004262162,0.2388623,0.001001748,0.0001785612,0.0004130457,0.007363428,0.00090748,0.01460999],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01273568,"threshold_uncertainty_score":0.02532315,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01924635109714334,"score_gpt":0.2972491321386542,"score_spread":0.2780027810415108,"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."}}