{"id":"W2962845353","doi":"","title":"Clustering with Same-Cluster Queries","year":2016,"lang":"en","type":"article","venue":"arXiv (Cornell University)","topic":"Machine Learning and Algorithms","field":"Computer Science","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Cluster analysis; Computer science; Time complexity; Margin (machine learning); Computational complexity theory; Theoretical computer science; Probabilistic logic; Correlation clustering; Cluster (spacecraft); Upper and lower bounds; Data mining; Mathematics; Algorithm; Artificial intelligence; 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":[0.007736278,0.001651197,0.003074485,0.001572542,0.00218107,0.004252117,0.008400766,0.004496038,0.005860769],"category_scores_gemma":[0.0299711,0.001279223,0.001954681,0.003469464,0.002556011,0.009973706,0.005541788,0.004413458,0.001925224],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002980338,"about_ca_system_score_gemma":0.003492614,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004850839,"about_ca_topic_score_gemma":0.006517474,"domain_scores_codex":[0.9877508,0.004645582,0.0006296397,0.003429463,0.002823087,0.000721553],"domain_scores_gemma":[0.9730157,0.01360193,0.001520036,0.008376104,0.002559632,0.000926519],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00123908,0.0008409288,0.003232442,0.0006837635,0.000325646,0.0004028682,0.001408944,0.4245818,0.007685557,0.2900373,0.03541116,0.2341506],"study_design_scores_gemma":[0.00005789241,0.00006898129,0.0002234755,0.00001331198,0.000020163,0.0001482737,0.0001273855,0.8589759,0.001959028,0.1340636,0.004309286,0.00003262936],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008531051,0.0002285608,0.986832,0.0009402825,0.00003893283,0.0002181187,0.000406227,0.001322414,0.001482433],"genre_scores_gemma":[0.2459851,0.0002036542,0.7474015,0.0006538373,0.0001879232,0.0005547341,0.002014486,0.0004382472,0.002560448],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008400766,"threshold_uncertainty_score":0.04091388,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02686987631801791,"score_gpt":0.1603286134564459,"score_spread":0.133458737138428,"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."}}