{"id":"W4281700085","doi":"10.1155/2022/2333497","title":"Integration and Application of Online Sports Resources Based on Multidimensional Intelligent Technology and Resource Optimization Architecture","year":2022,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"E-commerce and Technology Innovations","field":"Business, Management and Accounting","cited_by":3,"is_retracted":true,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Shared resource; Resource (disambiguation); Architecture; Cybernetics; Resource allocation; Computer science; Knowledge management; Campus network; Resource management (computing); Division (mathematics); Engineering management; Educational resources; Engineering; Computer network; Artificial intelligence; Sociology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":{"nature":"Retraction","reason":"Concerns/Issues about Data;Concerns/Issues about Results and/or Conclusions;Concerns/Issues about Referencing/Attributions;Concerns/Issues about Peer Review;Investigation by Journal/Publisher;Investigation by Third Party;Paper Mill;Computer-Aided Content or Computer-Generated Content;Unreliable Results and/or Conclusions;","date":"8/9/2023 0:00","openalex_flagged":true},"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005512525,0.0004952439,0.0005531067,0.001857879,0.0008828111,0.00238737,0.001033123,0.0004337981,0.002543445],"category_scores_gemma":[0.0009386391,0.0002313134,0.0006848171,0.001867122,0.0005006686,0.00315712,0.00227735,0.0003487887,0.000417659],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001034913,"about_ca_system_score_gemma":0.001544004,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007127773,"about_ca_topic_score_gemma":0.004845906,"domain_scores_codex":[0.999387,0.0001362462,0.00005422189,0.0001357264,0.0002035408,0.00008334802],"domain_scores_gemma":[0.9998116,0.00002800292,0.00002104674,0.00003802311,0.00006969877,0.00003162821],"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":[0.000246325,0.0004874381,0.01763334,0.0003056594,0.0002822978,0.000512944,0.001156181,0.2316945,0.02191276,0.1367437,0.007045543,0.5819793],"study_design_scores_gemma":[0.00003184395,0.0001242955,0.004915456,0.00005083557,0.0001572325,0.0001695337,0.0005476389,0.9249908,0.0089729,0.04089814,0.01907421,0.000067081],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1057325,0.0006408116,0.8509822,0.0005324637,0.00007822787,0.0003137913,0.0001391207,0.001876683,0.03970423],"genre_scores_gemma":[0.7976605,0.0006559695,0.19142,0.00009724051,0.00004323119,0.0002678582,0.0003758178,0.0001086285,0.009370691],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007127773,"threshold_uncertainty_score":0.01417255,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005578904883487188,"score_gpt":0.2231650649927372,"score_spread":0.21758616010925,"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."}}