{"id":"W4408000963","doi":"10.11834/jig.240739","title":"Continual testing time domain adaptive image classification method","year":2025,"lang":"en","type":"article","venue":"Journal of Image and Graphics","topic":"Advanced Measurement and Detection Methods","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"China Postdoctoral Science Foundation; National Natural Science Foundation of China; Canadian Institute for Advanced Research","keywords":"Image (mathematics); Computer science; Domain (mathematical analysis); Time domain; Artificial intelligence; Pattern recognition (psychology); Mathematics; Computer vision; Mathematical analysis","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009752826,0.000318237,0.0003303073,0.0006764908,0.0006342545,0.001556317,0.0006994022,0.0007061225,0.002822322],"category_scores_gemma":[0.003181405,0.0001425052,0.0003283447,0.0009065476,0.001136447,0.002987866,0.0006207465,0.0008962729,0.0004875937],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008030855,"about_ca_system_score_gemma":0.00107449,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007622627,"about_ca_topic_score_gemma":0.00358671,"domain_scores_codex":[0.999386,0.0001206274,0.00003439605,0.0001676114,0.0002357889,0.00005556004],"domain_scores_gemma":[0.9989789,0.0003758358,0.0000783892,0.00007797792,0.0004437875,0.00004511045],"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":[0.0002503546,0.0001890274,0.01688665,0.0003010487,0.0001110556,0.0003469212,0.002815897,0.06473429,0.02112156,0.1713808,0.01245668,0.7094057],"study_design_scores_gemma":[0.00009274484,0.0003120465,0.03105911,0.0001323849,0.0001876977,0.0007697912,0.004256095,0.7205007,0.02737052,0.1546398,0.06049516,0.0001839545],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2088505,0.002781463,0.6807598,0.003227771,0.0005074153,0.0001752854,0.0001932311,0.0009920181,0.1025125],"genre_scores_gemma":[0.9138362,0.001003039,0.06362768,0.0004002692,0.0001341418,0.0001073071,0.0001535475,0.00005833004,0.02067953],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007622627,"threshold_uncertainty_score":0.01515651,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02743343579116781,"score_gpt":0.3063804881163301,"score_spread":0.2789470523251623,"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."}}