{"id":"W4205769368","doi":"10.18280/ts.380627","title":"Image Feature Analysis and Dynamic Measurement of Plantar Pressure Based on Fusion Feature Extraction","year":2021,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Diabetic Foot Ulcer Assessment and Management","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Department of Science and Technology of Jilin Province; National Development and Reform Commission","keywords":"Plantar pressure; Feature extraction; Artificial intelligence; Pattern recognition (psychology); Computer science; Feature (linguistics); Image processing; Histogram; Image fusion; Computer vision; Footprint; Wavelet transform; Image (mathematics); Wavelet; Engineering; Pressure sensor; Geology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.0003121152,0.0005002636,0.0006539286,0.001642952,0.0001762692,0.0005971666,0.0003674459,0.0004515211,0.001053134],"category_scores_gemma":[0.0008621242,0.0001910393,0.0005231191,0.001224021,0.0002397504,0.0007963462,0.0004830378,0.0003152604,0.0003691117],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001465402,"about_ca_system_score_gemma":0.0001769941,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000569445,"about_ca_topic_score_gemma":0.0003687351,"domain_scores_codex":[0.9995286,0.00004024888,0.00003210211,0.0001145618,0.0002308139,0.0000537434],"domain_scores_gemma":[0.9996986,0.00006998675,0.00003900104,0.00004528235,0.0001284263,0.00001865268],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004038538,0.0001359965,0.00531111,0.0002365938,0.00007400837,0.0003591352,0.0001414508,0.00735828,0.3375372,0.000943501,0.001055485,0.6464435],"study_design_scores_gemma":[0.00006030089,0.001270609,0.07142351,0.00006344116,0.0002466383,0.0033302,0.0003571904,0.5516103,0.3619626,0.002963468,0.006547298,0.0001644719],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1451367,0.0006111487,0.8506582,0.00009626981,0.00008839482,0.0001017402,0.000227075,0.001190838,0.001889724],"genre_scores_gemma":[0.793855,0.0005946881,0.2037479,0.00006746624,0.00007734762,0.0001019348,0.000291724,0.0000633386,0.001200608],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001642952,"threshold_uncertainty_score":0.003523052,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01004432169812283,"score_gpt":0.2587239141378641,"score_spread":0.2486795924397412,"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."}}