{"id":"W2493818561","doi":"10.1007/978-3-319-25388-6_16","title":"The choice of a nearest neighbor estimate","year":2015,"lang":"en","type":"book-chapter","venue":"Springer series in the data sciences","topic":"Machine Learning and Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Minimax; Mathematics; k-nearest neighbors algorithm; Nonparametric statistics; Class (philosophy); Universality (dynamical systems); Convergence (economics); Nonparametric regression; Property (philosophy); Function (biology); Applied mathematics; Econometrics; Statistics; Computer science; Mathematical economics; Artificial intelligence; Economics; Physics","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":["open_science"],"consensus_categories":[],"category_scores_codex":[0.003630645,0.0002357155,0.0002512668,0.0000996953,0.0004931518,0.0006644377,0.01335851,0.00007640907,0.00001584684],"category_scores_gemma":[0.000516979,0.0001224558,0.00004190376,0.000249398,0.001330532,0.0008924885,0.00318122,0.0004767413,0.00003896046],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000164716,"about_ca_system_score_gemma":0.0002807115,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003211514,"about_ca_topic_score_gemma":0.0004439293,"domain_scores_codex":[0.9976581,0.00009108565,0.0003534287,0.000638777,0.0009194682,0.0003391279],"domain_scores_gemma":[0.9963577,0.0005664942,0.0003308368,0.002619896,0.00007440797,0.00005063262],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000005843834,0.00001332883,0.0002305156,0.00002958937,0.00001654344,0.00001905295,0.0007427518,0.0003211905,0.000002878002,0.9338478,0.006175131,0.05859535],"study_design_scores_gemma":[0.00009093647,0.0001535259,0.0005311204,0.0001470792,0.00001161017,0.00002981988,0.00007038063,0.02996435,0.000005835185,0.04955583,0.9191585,0.0002810189],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0002960774,0.01313122,0.01052247,0.0206988,0.005346485,0.0009670454,0.000452412,0.0003086518,0.9482768],"genre_scores_gemma":[0.06011591,0.005730501,0.3060454,0.002470647,0.005414524,0.0001468641,0.0004897729,0.0002920633,0.6192943],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.9129834,"threshold_uncertainty_score":0.9919797,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09872209417537257,"score_gpt":0.3468970555342034,"score_spread":0.2481749613588308,"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."}}