{"id":"W4407129098","doi":"10.1109/tce.2025.3536438","title":"PDFormer: Efficient Vision Transformer for Photovoltaic Defect Detection","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Consumer Electronics","topic":"Industrial Vision Systems and Defect Detection","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"National Natural Science Foundation of China","keywords":"Photovoltaic system; Transformer; Electrical engineering; Computer science; Electronic engineering; Voltage; Computer vision; Engineering","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":[0.0007434304,0.00114398,0.0007653576,0.001200235,0.0002225451,0.0006765028,0.00206264,0.0009090175,0.002973295],"category_scores_gemma":[0.001714881,0.0003431588,0.000667988,0.0005872306,0.0003413199,0.001518922,0.001196259,0.001004545,0.002051051],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005549325,"about_ca_system_score_gemma":0.0008234127,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002900593,"about_ca_topic_score_gemma":0.00621198,"domain_scores_codex":[0.9995839,0.00003883567,0.0000148896,0.0001473231,0.0001590513,0.00005598265],"domain_scores_gemma":[0.9996731,0.00008089501,0.00003408639,0.00007835314,0.0001041804,0.00002944535],"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":[0.000272292,0.000266661,0.002882823,0.0001992262,0.00008633437,0.00015779,0.00004063902,0.02483153,0.04095687,0.001950008,0.02365171,0.9047042],"study_design_scores_gemma":[0.00007719026,0.0003198444,0.002115813,0.00001960463,0.00004119331,0.0005301585,0.00003807078,0.9301952,0.05539265,0.003058926,0.008183671,0.00002776036],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08343405,0.001366845,0.8631387,0.0003425105,0.0002262943,0.0003854437,0.001898051,0.0437361,0.005471888],"genre_scores_gemma":[0.496874,0.0007787736,0.4808854,0.0005409862,0.00009856669,0.0002297377,0.008582244,0.0006547421,0.01135569],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002973295,"threshold_uncertainty_score":0.009946644,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007688148377656624,"score_gpt":0.2432748100262971,"score_spread":0.2355866616486404,"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."}}