{"id":"W32592253","doi":"10.1007/3-540-45105-6_38","title":"PalmPrints: A Novel Co-evolutionary Algorithm for Clustering Finger Images","year":2003,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"","keywords":"Cluster analysis; Computer science; Fitness function; Artificial intelligence; Genetic algorithm; Correlation clustering; Pattern recognition (psychology); Evolutionary algorithm; Canopy clustering algorithm; Algorithm; Machine learning","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":[0.001134632,0.001017499,0.001694286,0.001606527,0.0007963986,0.001246718,0.002649784,0.002060149,0.003533213],"category_scores_gemma":[0.002203701,0.0007328154,0.0009113216,0.002432325,0.0006943396,0.001530588,0.001668069,0.001270888,0.00143193],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000570612,"about_ca_system_score_gemma":0.0008532042,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003595095,"about_ca_topic_score_gemma":0.004984521,"domain_scores_codex":[0.9991278,0.0001333321,0.00004101213,0.0002017054,0.0004215657,0.00007471775],"domain_scores_gemma":[0.9991972,0.0002599849,0.00005956222,0.0001368382,0.0002930301,0.00005342994],"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":[0.0001848273,0.0001399678,0.001223375,0.0001131037,0.0001811613,0.0001403363,0.0001399184,0.1608135,0.02483582,0.004868441,0.004867903,0.8024917],"study_design_scores_gemma":[0.00002767135,0.00005566954,0.0004189173,0.00001027585,0.00002882784,0.0001813322,0.000023369,0.9869542,0.006628643,0.002349577,0.003297734,0.00002371248],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.007289819,0.0002192767,0.9905905,0.00005559342,0.00006824126,0.00003993014,0.00003292259,0.0008830323,0.0008206465],"genre_scores_gemma":[0.06713752,0.000194064,0.9273261,0.0001161774,0.00005231947,0.000131595,0.0001431992,0.0002917517,0.004607245],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003595095,"threshold_uncertainty_score":0.01181978,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02376040507155295,"score_gpt":0.2710031404315853,"score_spread":0.2472427353600324,"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."}}