{"id":"W3176752316","doi":"10.1093/database/baab035","title":"Which methods are the most effective in enabling novice users to participate in ontology creation? A usability study","year":2021,"lang":"en","type":"article","venue":"Database","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa; Government of Canada; Agriculture and Agri-Food Canada; University of Manitoba","funders":"Canadian Institutes of Health Research; National Science Foundation","keywords":"Usability; Wizard; Computer science; Ontology; Interoperability; World Wide Web; Set (abstract data type); Think aloud protocol; Data curation; Data science; Information retrieval; Human–computer interaction","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001546287,0.0001168705,0.0002040718,0.00004563285,0.00005524246,0.00001861154,0.0001846844,0.0000929211,0.00001446047],"category_scores_gemma":[0.005722214,0.00008842239,0.00002315313,0.0005720299,0.0000721802,0.000004131177,0.0002951084,0.0001810981,0.000005441865],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002957826,"about_ca_system_score_gemma":0.00009091361,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001005001,"about_ca_topic_score_gemma":0.04623492,"domain_scores_codex":[0.9978415,0.001076344,0.0002369733,0.0004881335,0.00009076105,0.0002662638],"domain_scores_gemma":[0.9988803,0.0003341171,0.00004689219,0.0005747729,0.00009487208,0.00006908261],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003405827,0.001082018,0.8694698,0.00004170467,0.00006879904,0.00008941861,0.002384549,0.0002288002,0.09090616,0.00002345916,0.0003086142,0.03505605],"study_design_scores_gemma":[0.001826471,0.000485881,0.8953944,0.0000662492,0.00004324658,0.00001310318,0.01940522,0.000382283,0.06909525,0.00004688991,0.01293773,0.0003032176],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9954387,0.000282583,0.002447256,0.001196104,0.00009129749,0.0003824604,0.00006999625,0.000009189432,0.00008244498],"genre_scores_gemma":[0.9946734,0.00001630131,0.004295147,0.0005669033,0.00004084574,0.0002285386,0.0001495373,0.000007380435,0.00002193609],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04522992,"threshold_uncertainty_score":0.9711688,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03992296776808297,"score_gpt":0.4024975044328333,"score_spread":0.3625745366647504,"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."}}