{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001041306,0.00009626014,0.0001879978,0.0002443854,0.00006913347,0.00004054383,0.00005974175,0.00005460438,0.00000589195],"category_scores_gemma":[0.0002842625,0.00008559103,0.00006441909,0.0003770439,0.00004500102,0.0002865916,0.00001019368,0.0002842508,0.000001377679],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002127324,"about_ca_system_score_gemma":0.00001885246,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":5.640347e-7,"about_ca_topic_score_gemma":5.265769e-7,"domain_scores_codex":[0.9992928,0.00008656755,0.0003093249,0.00007276,0.0001288463,0.0001097345],"domain_scores_gemma":[0.9991637,0.0002748457,0.0001198659,0.00007135385,0.0003205895,0.00004967714],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00004447817,0.00001790363,0.0002760724,0.00004083878,0.00008543425,0.00001207514,0.0001213018,0.0001047094,0.9186859,0.0009367314,0.001330667,0.07834393],"study_design_scores_gemma":[0.009417661,0.00136931,0.07395146,0.001551753,0.001006502,0.0006790531,0.004093426,0.2336925,0.3862627,0.2433343,0.04287136,0.00176999],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01326557,0.0006954383,0.980038,0.00009402767,0.0001794926,0.00005823452,0.000002071297,0.00004157889,0.005625559],"genre_scores_gemma":[0.03093245,0.0001423365,0.9685763,0.00007286749,0.0001209861,0.000002000033,4.560306e-7,0.00001385143,0.0001387107],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.5324232,"threshold_uncertainty_score":0.3490301,"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."}}