{"id":"W4285781363","doi":"10.1002/widm.1343","title":"Density‐based clustering","year":2019,"lang":"en","type":"article","venue":"Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery","topic":"Advanced Clustering Algorithms Research","field":"Computer Science","cited_by":116,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Cluster analysis; 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":[0.003838481,0.00129238,0.00220873,0.007239121,0.00193558,0.005234365,0.00326446,0.002048587,0.005479062],"category_scores_gemma":[0.01620496,0.0009715724,0.001876872,0.008456771,0.002068645,0.004136845,0.003505504,0.002225565,0.004590356],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003100173,"about_ca_system_score_gemma":0.002988806,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008484232,"about_ca_topic_score_gemma":0.006032702,"domain_scores_codex":[0.9949263,0.001283402,0.0003007831,0.001261996,0.00197574,0.0002517191],"domain_scores_gemma":[0.9935732,0.002282191,0.0005390351,0.001218934,0.002226437,0.0001600937],"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":[0.0001408121,0.00009933129,0.007816515,0.001292713,0.0005144815,0.0002478856,0.001063313,0.1986971,0.004724952,0.3514377,0.05352438,0.380441],"study_design_scores_gemma":[0.00002663183,0.00004443609,0.004098123,0.0003759955,0.0001059325,0.0004559251,0.0004699687,0.5812464,0.004608578,0.314015,0.09439316,0.0001597448],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.004099802,0.002668845,0.982375,0.0007011472,0.0001699624,0.0001955536,0.001005308,0.0009771847,0.007807297],"genre_scores_gemma":[0.2004357,0.007931127,0.7709983,0.0007484067,0.0005505387,0.0006167406,0.006550762,0.0009230143,0.01124531],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.008484232,"threshold_uncertainty_score":0.02249342,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06673601290054507,"score_gpt":0.3667671650858934,"score_spread":0.3000311521853484,"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."}}