{"id":"W4323363529","doi":"10.1093/iwc/iwad019","title":"Evaluating Visual Analytics for Relevant Information Retrieval in Document Collections","year":2023,"lang":"en","type":"article","venue":"Interacting with Computers","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Conselho Nacional de Desenvolvimento Científico e Tecnológico; Fundação de Amparo à Pesquisa do Estado de São Paulo","keywords":"Computer science; Information retrieval; Visual analytics; Recall; Analytics; Precision and recall; Perspective (graphical); Process (computing); Data science; World Wide Web; Visualization; Data mining; Artificial intelligence; Psychology","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":[0.01383854,0.0009209772,0.0007522373,0.006877382,0.0006883364,0.005716259,0.001204835,0.001098469,0.003016586],"category_scores_gemma":[0.1185554,0.0003214834,0.0009344402,0.003117149,0.0006435685,0.003883729,0.002368615,0.0009487536,0.0007866859],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001328786,"about_ca_system_score_gemma":0.0008265809,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003231623,"about_ca_topic_score_gemma":0.002362879,"domain_scores_codex":[0.9902601,0.005562539,0.0009411619,0.0008077784,0.002159213,0.0002692211],"domain_scores_gemma":[0.8567971,0.1195451,0.007490419,0.005044959,0.008715362,0.002407146],"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":[0.01313227,0.004095771,0.1322882,0.009643774,0.001704151,0.0005216001,0.01224997,0.0427742,0.03092629,0.00507517,0.02117208,0.7264164],"study_design_scores_gemma":[0.001460817,0.01062722,0.2069805,0.002088519,0.001446033,0.001075885,0.01030566,0.6815233,0.04395064,0.01858626,0.02139534,0.0005597688],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9400236,0.002736519,0.04168754,0.0005902778,0.0001291009,0.001544897,0.001747713,0.004889425,0.006650798],"genre_scores_gemma":[0.9374948,0.0004149071,0.05919485,0.00009444205,0.00004674846,0.0003477818,0.001825865,0.0001411435,0.0004395278],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01383854,"threshold_uncertainty_score":0.0731861,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04359985564566519,"score_gpt":0.3863054692844198,"score_spread":0.3427056136387546,"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."}}