{"id":"W128276880","doi":"10.1007/3-540-33880-2_9","title":"Visually Exploring Concept-Based Fuzzy Clusters in Web Search Results","year":2006,"lang":"en","type":"book-chapter","venue":"Studies in computational intelligence","topic":"Image Retrieval and Classification Techniques","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Regina","funders":"","keywords":"Computer science; Information retrieval; Cluster analysis; Relevance (law); Data mining; Set (abstract data type); Sorting; Selection (genetic algorithm); Fuzzy clustering; Task (project management); Centroid; Web page; Machine learning; Artificial intelligence; World Wide Web; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007932517,0.0004171749,0.0005224679,0.0007531887,0.0001220973,0.0001011614,0.001107361,0.0001720828,0.000008531765],"category_scores_gemma":[0.000148206,0.0004300934,0.0001303786,0.0004303533,0.0005547344,0.0003358761,0.0005019314,0.0006444523,0.00007191842],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006054784,"about_ca_system_score_gemma":0.000402832,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002858254,"about_ca_topic_score_gemma":0.00006478377,"domain_scores_codex":[0.9965573,0.0000921656,0.001143341,0.0009397112,0.0008764571,0.0003910436],"domain_scores_gemma":[0.9972484,0.001344308,0.000285331,0.0004424239,0.0006206487,0.00005895444],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001062591,0.000155852,0.00004281304,0.0002254135,0.00008211319,0.0002907415,0.00253721,0.2411104,0.00001033286,0.6586996,0.00308856,0.09365072],"study_design_scores_gemma":[0.0009515114,0.0005375751,0.0003122779,0.003513809,0.00001915755,0.00002207403,0.000649137,0.6798388,0.002513772,0.2942203,0.01534525,0.00207631],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00003926631,0.002789968,0.8978326,0.001673272,0.0007044049,0.0007272315,0.00005767137,0.0003298193,0.09584576],"genre_scores_gemma":[0.7423995,0.003530768,0.184611,0.001580187,0.0006307198,0.0004505223,0.0003627313,0.000175183,0.0662594],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7423602,"threshold_uncertainty_score":0.9998151,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2096020817133564,"score_gpt":0.3819612114665424,"score_spread":0.172359129753186,"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."}}