{"id":"W3108390127","doi":"","title":"ScholarLensViz: A Visualization Framework for Transparency in Semantic User Profiles","year":2020,"lang":"en","type":"article","venue":"International Semantic Web Conference","topic":"Advanced Text Analysis Techniques","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Transparency (behavior); Visualization; Data visualization; Human–computer interaction; Data mining; Computer security","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":[0.002514694,0.001638098,0.001011291,0.005016152,0.001292982,0.005637456,0.001661845,0.001336495,0.0191437],"category_scores_gemma":[0.008867356,0.0008943438,0.001431951,0.003554704,0.0006187435,0.006637285,0.00522545,0.00262819,0.005497316],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001027969,"about_ca_system_score_gemma":0.001791859,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00851051,"about_ca_topic_score_gemma":0.01299614,"domain_scores_codex":[0.9986059,0.0003571576,0.0001667184,0.0001966993,0.0005292156,0.0001443615],"domain_scores_gemma":[0.9967682,0.001206131,0.0002619785,0.0009293731,0.0005631409,0.0002711952],"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":[0.00177666,0.0004229716,0.006289024,0.002147376,0.0003125726,0.000822306,0.009650614,0.0130945,0.02080129,0.1968268,0.2419163,0.5059396],"study_design_scores_gemma":[0.0002449811,0.0001278215,0.003053218,0.0007586024,0.0001910411,0.0004587442,0.001727565,0.1839853,0.03923953,0.1817546,0.5881538,0.0003047331],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.007568642,0.0002892264,0.7901289,0.0008954591,0.0002328216,0.0002951959,0.01606054,0.1749306,0.009598596],"genre_scores_gemma":[0.2085627,0.001119529,0.7091812,0.0006808164,0.0002105312,0.001077329,0.03219814,0.03115408,0.01581568],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0191437,"threshold_uncertainty_score":0.06404203,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04154389703295188,"score_gpt":0.3333822274307985,"score_spread":0.2918383303978467,"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."}}