{"id":"W4400485152","doi":"10.61091/jcmcc120-30","title":"Multi-Scale Deep Learning-Based University Financial System: Hardware Design and Database Integration","year":2024,"lang":"en","type":"article","venue":"Journal of Combinatorial Mathematics and Combinatorial Computing","topic":"Stock Market Forecasting Methods","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Inner Mongolia University of Technology; Inner Mongolia University","keywords":"Computer science; Scale (ratio); Computer architecture; Deep learning; Computer hardware; Database; Artificial intelligence; Cartography; Geography","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":[0.0003654149,0.0003863272,0.0003678865,0.0003973407,0.0003498026,0.0008786609,0.001656338,0.0005789459,0.003096425],"category_scores_gemma":[0.0007043291,0.000280866,0.0003356033,0.0004420585,0.0002641522,0.001425158,0.0007233612,0.0004965047,0.0006737107],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008084429,"about_ca_system_score_gemma":0.0009328186,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00387927,"about_ca_topic_score_gemma":0.004041926,"domain_scores_codex":[0.9996406,0.00003737151,0.00003562078,0.0001073986,0.0001240913,0.00005497181],"domain_scores_gemma":[0.9997465,0.00003433948,0.00002519019,0.00004790558,0.000114919,0.00003126216],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006497597,0.000593613,0.009923757,0.0004076385,0.0001923595,0.0004294758,0.0002413262,0.1978227,0.08949576,0.01001523,0.01378273,0.6764457],"study_design_scores_gemma":[0.0000404255,0.0002076956,0.001866158,0.00001352466,0.00004423313,0.0001880147,0.00002991015,0.967045,0.02395831,0.001857923,0.004716105,0.00003272243],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.08726402,0.0004932637,0.8981978,0.0005497523,0.0001364377,0.0002809718,0.0002433548,0.005671459,0.007162911],"genre_scores_gemma":[0.8455829,0.0002329029,0.149502,0.000307479,0.00003974718,0.0002433371,0.0003529543,0.00005290391,0.00368585],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00387927,"threshold_uncertainty_score":0.01035857,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05920111622378692,"score_gpt":0.3259984833205339,"score_spread":0.266797367096747,"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."}}