{"id":"W2147876569","doi":"10.1109/tkde.2015.2453171","title":"RankRC: Large-Scale Nonlinear Rare Class Ranking","year":2015,"lang":"en","type":"article","venue":"IEEE Transactions on Knowledge and Data Engineering","topic":"Domain Adaptation and Few-Shot Learning","field":"Computer Science","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Robustness (evolution); Kernel (algebra); Machine learning; Artificial intelligence; Focus (optics); Class (philosophy); Nonlinear system; Rare events; Algorithm; Computational complexity theory; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.004577007,0.001173652,0.00206592,0.001690308,0.001052807,0.002350374,0.003020836,0.002185794,0.003967816],"category_scores_gemma":[0.01490596,0.000438874,0.0008999616,0.001387311,0.001273424,0.00307397,0.002750654,0.002479194,0.002851157],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001093319,"about_ca_system_score_gemma":0.001906913,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003333721,"about_ca_topic_score_gemma":0.004138499,"domain_scores_codex":[0.9966751,0.001180379,0.0001613686,0.0005457434,0.001158357,0.0002790487],"domain_scores_gemma":[0.993258,0.002465226,0.0006489971,0.001930773,0.001405256,0.0002917683],"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":[0.0004838559,0.0004735461,0.002579386,0.0003290133,0.000146666,0.0002509505,0.0001757501,0.2211362,0.009610462,0.03754511,0.03168866,0.6955804],"study_design_scores_gemma":[0.00002588075,0.0001027312,0.0003540216,0.0000105435,0.00001170678,0.0001400602,0.00002966196,0.9795111,0.003635542,0.01377923,0.002375022,0.00002436884],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01646646,0.0003219786,0.9778265,0.0003190452,0.00008279479,0.0001498652,0.0002312261,0.003042616,0.001559528],"genre_scores_gemma":[0.3727706,0.0003319029,0.6167295,0.0004934108,0.0002044947,0.0003560472,0.00176154,0.0006580561,0.006694471],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004577007,"threshold_uncertainty_score":0.02420586,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03825382451170466,"score_gpt":0.2748310372290403,"score_spread":0.2365772127173357,"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."}}