{"meta":{"query_hash":"7221a553e27c","filters":{"venue":"Learning with Imbalanced Domains: Theory and Applications"},"cohort_total":1,"direct_labels_cover":0,"predictions_cover":1,"exported":1,"export_cap":100000,"truncated":false,"label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"permalink":"https://metacan.xera.ac/q/7221a553e27c","api":"https://metacan.xera.ac/api/v1/cohort?venue=Learning+with+Imbalanced+Domains%3A+Theory+and+Applications"},"results":[{"id":"W2774222091","doi":"","title":"Sampling a Longer Life: Binary versus One-class classification Revisited","year":2017,"lang":"en","type":"article","venue":"Learning with Imbalanced Domains: Theory and Applications","topic":"Imbalanced Data Classification Techniques","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa; University of Alberta","funders":"","keywords":"Class (philosophy); Binary number; Sampling (signal processing); Computer science; Statistics; Mathematics; Artificial intelligence; Arithmetic; Computer vision","score_opus":0.03681048116922473,"score_gpt":0.3051340556227185,"score_spread":0.26832357445349375,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2774222091","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10799452,0.010841002,0.8432823,0.028610915,0.0019098667,0.00020719005,0.000417574,0.0003977624,0.0063389484],"genre_scores_gemma":[0.80079496,0.0046926807,0.17056632,0.0054872967,0.0062245377,0.0005052262,0.0008233858,0.0003704116,0.010535333],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9849889,0.008876489,0.00058741163,0.0024768387,0.0025181067,0.000552227],"domain_scores_gemma":[0.83874273,0.13497481,0.0044802185,0.012622584,0.0059046634,0.0032750906],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.04279398,0.0010540803,0.0034871423,0.0023042862,0.0021859112,0.004276773,0.006193013,0.005811201,0.005373883],"category_scores_gemma":[0.17757618,0.0008690738,0.0014523352,0.0030224118,0.006053389,0.019841217,0.0045378306,0.009547127,0.00077952835],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00087372935,0.00043554656,0.01438314,0.00057512766,0.00023542068,0.00030407502,0.001675751,0.036858756,0.0007243698,0.6052271,0.024188604,0.3145184],"study_design_scores_gemma":[0.00008998026,0.00012794544,0.002495391,0.00017142459,0.00006424923,0.00033041666,0.00042492422,0.36207485,0.00043110733,0.6288439,0.0049003838,0.000045342666],"about_ca_topic_score_codex":0.002266812,"about_ca_topic_score_gemma":0.0024317754,"teacher_disagreement_score":0.04279398,"about_ca_system_score_codex":0.0029598272,"about_ca_system_score_gemma":0.0014127883,"threshold_uncertainty_score":0.2263189},"labels":[],"label_agreement":null}]}