{"id":"W7045507979","doi":"","title":"An analysis of semi-supervised learning with the Guelph Cluster Class algorithm","year":2002,"lang":"en","type":"dissertation","venue":"The Atrium (University of Guelph)","topic":"Machine Learning and Data Classification","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Cluster analysis; Classifier (UML); Remainder; Class (philosophy); Cluster (spacecraft); Statistical classification; Fuzzy clustering; Selection (genetic algorithm)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.02396125,0.001037482,0.001862709,0.004430891,0.002507785,0.003716516,0.003927171,0.002329849,0.002770372],"category_scores_gemma":[0.07836366,0.0008596355,0.001429998,0.004203306,0.005152826,0.005138021,0.003324061,0.003233329,0.0008291755],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006014139,"about_ca_system_score_gemma":0.003872493,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01351627,"about_ca_topic_score_gemma":0.009626962,"domain_scores_codex":[0.9838837,0.008120178,0.0004731131,0.001841855,0.005223351,0.0004578836],"domain_scores_gemma":[0.9374751,0.04869303,0.002248333,0.002993915,0.008031479,0.0005581705],"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":[0.0004072697,0.0001470933,0.008363358,0.0003582125,0.0002946786,0.0001679016,0.001115949,0.3354499,0.000943214,0.4169683,0.009706196,0.226078],"study_design_scores_gemma":[0.00001504756,0.00005164475,0.000824367,0.00004681122,0.00001864104,0.00005680278,0.00006746654,0.9113091,0.0004804008,0.08488343,0.002225042,0.00002127934],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01321951,0.001222908,0.9787482,0.0009466884,0.00007769243,0.0002322777,0.00008829367,0.0004550891,0.005009331],"genre_scores_gemma":[0.3388994,0.001231335,0.651123,0.0006343674,0.000417443,0.0007683397,0.000619988,0.0005037732,0.005802411],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02396125,"threshold_uncertainty_score":0.1267208,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01180296466771591,"score_gpt":0.2260484454404272,"score_spread":0.2142454807727113,"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."}}