{"id":"W4409363292","doi":"10.1609/aaai.v39i20.35489","title":"Revisiting Interpolation for Noisy Label Correction","year":2025,"lang":"en","type":"article","venue":"Proceedings of the AAAI Conference on Artificial Intelligence","topic":"Digital Filter Design and Implementation","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Wuhan University","keywords":"Interpolation (computer graphics); Computer science; Artificial intelligence; Mathematics; Algorithm","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":[0.003920162,0.001377945,0.001178899,0.001527589,0.0009045278,0.001434134,0.002850448,0.001729643,0.002411785],"category_scores_gemma":[0.01351961,0.0005672308,0.0008123911,0.00125694,0.002180287,0.003369639,0.003003333,0.003407598,0.001525981],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001250505,"about_ca_system_score_gemma":0.001756494,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002343951,"about_ca_topic_score_gemma":0.003443049,"domain_scores_codex":[0.9977657,0.0005689975,0.0001044019,0.0005936171,0.0008217522,0.0001455633],"domain_scores_gemma":[0.9942967,0.002212149,0.0005330093,0.001627033,0.001138731,0.0001923177],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0004332562,0.0002043678,0.00313685,0.0003449622,0.0001031509,0.0001913734,0.0004711167,0.1347688,0.05240074,0.03927979,0.008026903,0.7606387],"study_design_scores_gemma":[0.00003242049,0.0001278948,0.0006710379,0.00003661285,0.00002714364,0.000192123,0.0000504045,0.9323226,0.03095851,0.02960759,0.005928961,0.00004459114],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01453414,0.0004570984,0.9808257,0.0003380401,0.0001171282,0.00004909001,0.00006801629,0.002207808,0.001402866],"genre_scores_gemma":[0.3051687,0.0005904311,0.6869256,0.000686656,0.0003302218,0.0001364143,0.0003686262,0.0006773142,0.005115999],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003920162,"threshold_uncertainty_score":0.0207321,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09964741772583845,"score_gpt":0.3444744767381347,"score_spread":0.2448270590122963,"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."}}