{"id":"W4406250240","doi":"10.18280/ts.410638","title":"Image Classification and Retrieval of TCM Materials Based on Feature Enhancement","year":2024,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Advanced Computing and Algorithms","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Hubei University","keywords":"Feature (linguistics); Pattern recognition (psychology); Computer science; Artificial intelligence; Information retrieval","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":[0.0004484622,0.0007133877,0.0008678569,0.002828917,0.0003074143,0.0007951129,0.000616138,0.0007763008,0.001487582],"category_scores_gemma":[0.0008767922,0.0002407723,0.001207127,0.001678937,0.0004094306,0.001077783,0.00043353,0.0005276999,0.0009667819],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004124685,"about_ca_system_score_gemma":0.0005672346,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002121003,"about_ca_topic_score_gemma":0.002206841,"domain_scores_codex":[0.9996729,0.00002265702,0.00002633564,0.00009279239,0.0001233675,0.00006194903],"domain_scores_gemma":[0.9996736,0.00005419406,0.00004433444,0.00004858725,0.0001601041,0.00001922577],"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":[0.0005359881,0.0001605464,0.001780133,0.0003548168,0.00007623188,0.000328284,0.0001069676,0.01271605,0.4068466,0.001959626,0.003852578,0.5712823],"study_design_scores_gemma":[0.00005445,0.0004853118,0.01597599,0.00004764656,0.0002307539,0.0009952853,0.0001436059,0.689736,0.28042,0.002542438,0.009275907,0.00009261004],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1440568,0.001779313,0.8444597,0.0003685184,0.0001717674,0.0003486122,0.0005411562,0.003576993,0.004697116],"genre_scores_gemma":[0.4555915,0.001749365,0.5340118,0.0003264892,0.0001591305,0.0002528556,0.001303448,0.0002281224,0.006377389],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002828917,"threshold_uncertainty_score":0.004976451,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02079582882662831,"score_gpt":0.307911707170955,"score_spread":0.2871158783443267,"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."}}