{"id":"W4292510811","doi":"10.6087/kcse.285","title":"Improving Journal Article Tag Suite for multilingual articles","year":2022,"lang":"en","type":"article","venue":"Science Editing","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"U.S. National Library of Medicine; Canadian Medical Association","keywords":"Suite; Computer science; Variety (cybernetics); Set (abstract data type); World Wide Web; Information retrieval; Library science; Data science; Political science; Artificial intelligence; Programming language; Law","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.04456,0.002303504,0.002113204,0.020749,0.003888516,0.01432217,0.003780182,0.0026153,0.01937398],"category_scores_gemma":[0.1624307,0.002762435,0.002466159,0.01245809,0.00204044,0.02201852,0.007296583,0.006073353,0.04148195],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003322766,"about_ca_system_score_gemma":0.009386496,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00610758,"about_ca_topic_score_gemma":0.00835843,"domain_scores_codex":[0.9646668,0.01051986,0.009254289,0.002923167,0.0113452,0.001290686],"domain_scores_gemma":[0.6988826,0.0616348,0.01813776,0.06846412,0.1430328,0.009847932],"domain_codex":null,"domain_gemma":"reporting","domain_candidate":"reporting","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0009032635,0.0007492607,0.009069917,0.001771395,0.0002152182,0.001181217,0.003437042,0.003579944,0.06093587,0.02006168,0.256029,0.6420663],"study_design_scores_gemma":[0.0002105895,0.0005222978,0.005631893,0.0006274128,0.0002548877,0.001540026,0.002133562,0.03241908,0.08382942,0.01398583,0.8582267,0.0006183466],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01523626,0.0007245102,0.8062707,0.005849253,0.004155728,0.002871764,0.006581593,0.1469533,0.01135703],"genre_scores_gemma":[0.03061653,0.000775561,0.8972658,0.001900762,0.001148345,0.0009400282,0.02631026,0.02416784,0.01687475],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9856778,"threshold_uncertainty_score":0.2356586,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01536239155432406,"score_gpt":0.2954643337713264,"score_spread":0.2801019422170024,"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."}}