{"id":"W2966173742","doi":"","title":"Visualization for Text Mining in the Digital Humanities - Empowering Researchers to Use Advanced Tools for Text Mining.","year":2017,"lang":"en","type":"article","venue":"Ingénierie des systèmes d information","topic":"Digital Humanities and Scholarship","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Digital humanities; Visualization; Data science; Computer science; Text mining; Biomedical text mining; World Wide Web; Information retrieval; Natural language processing; Data mining","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008663998,0.001681812,0.001125361,0.009445476,0.001585337,0.007750412,0.001918615,0.001900579,0.019749],"category_scores_gemma":[0.04481826,0.0007820764,0.001188275,0.009461148,0.001032238,0.009806723,0.00400124,0.002408409,0.008958287],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009131047,"about_ca_system_score_gemma":0.002499134,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002002378,"about_ca_topic_score_gemma":0.00336067,"domain_scores_codex":[0.994869,0.002336631,0.0008219508,0.0005869471,0.001250876,0.0001346353],"domain_scores_gemma":[0.958577,0.02837746,0.002728192,0.004717252,0.004556939,0.001043117],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0007927949,0.0004284719,0.006057831,0.005116097,0.0003933837,0.0008193397,0.004600127,0.003229836,0.02070429,0.0618381,0.2693506,0.6266691],"study_design_scores_gemma":[0.0003041232,0.0002697071,0.00738813,0.002970296,0.0003319945,0.00161188,0.003115356,0.1115241,0.049108,0.2966943,0.5264357,0.0002464453],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01660375,0.008205445,0.7302359,0.01347855,0.001891403,0.000982257,0.0488199,0.1611923,0.01859043],"genre_scores_gemma":[0.08771224,0.004083262,0.8682979,0.001117331,0.0006899736,0.001011361,0.02265842,0.005864211,0.008565179],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.019749,"threshold_uncertainty_score":0.06606704,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1488259026535591,"score_gpt":0.3299429979739371,"score_spread":0.181117095320378,"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."}}