{"id":"W2041676769","doi":"10.1142/s0218843008001932","title":"EVOLVING A SOCIAL VISUALIZATION DESIGN AIMED AT INCREASING PARTICIPATION IN A CLASS-BASED ONLINE COMMUNITY","year":2008,"lang":"en","type":"article","venue":"International Journal of Cooperative Information Systems","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Telus (Canada); University of Saskatchewan","funders":"","keywords":"Visualization; Computer science; Cluster analysis; Personalization; Class (philosophy); Human–computer interaction; Information visualization; Online community; Visual analytics; World Wide Web; Data science; Artificial intelligence","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":[0.004188005,0.001246712,0.0005351066,0.001500062,0.0009828855,0.003167914,0.001483917,0.001220339,0.004988429],"category_scores_gemma":[0.0125578,0.0005005847,0.0007123941,0.0007305413,0.0009048747,0.002764507,0.002235255,0.001334909,0.0008022824],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006534368,"about_ca_system_score_gemma":0.0007279158,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005851271,"about_ca_topic_score_gemma":0.001045587,"domain_scores_codex":[0.9973327,0.001558538,0.000126539,0.0003703689,0.0004447776,0.000167162],"domain_scores_gemma":[0.9917064,0.003613942,0.0004437128,0.001544958,0.001728237,0.0009627827],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.002153291,0.003663287,0.02287468,0.002513496,0.0003577214,0.001163051,0.03356325,0.01525692,0.1575604,0.03712149,0.02332395,0.7004485],"study_design_scores_gemma":[0.002462282,0.01000752,0.06069594,0.001182562,0.001211688,0.003398235,0.01445175,0.2273077,0.1318477,0.07644238,0.4699681,0.001023978],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2920587,0.000378718,0.6796015,0.002130371,0.000532407,0.001268413,0.0003479095,0.01007682,0.01360511],"genre_scores_gemma":[0.4819672,0.0001838146,0.5087049,0.0002519489,0.0001189966,0.001261302,0.0003309822,0.0009488086,0.006232152],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004988429,"threshold_uncertainty_score":0.02214855,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07463535164154282,"score_gpt":0.369346390320168,"score_spread":0.2947110386786251,"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."}}