{"id":"W4409605078","doi":"10.61091/jcmcc127b-325","title":"Detection of Mental Training Anxiety in Basketball Players in Same-Court Rivalry Centers Based on LightGBM Algorithm","year":2025,"lang":"en","type":"article","venue":"Journal of Combinatorial Mathematics and Combinatorial Computing","topic":"AI and Big Data Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Basketball; Rivalry; Anxiety; Training (meteorology); Psychology; Computer science; Artificial intelligence; Applied psychology; Algorithm; Speech recognition; Machine learning; Psychiatry; Economics; History; 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":[0.0003540865,0.0005759705,0.0004279532,0.001205493,0.0002440617,0.0005015934,0.0004277385,0.0003381614,0.001066821],"category_scores_gemma":[0.00119733,0.0001205148,0.0005262014,0.0005938729,0.000188143,0.0003427968,0.000507253,0.000340844,0.000317891],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004092533,"about_ca_system_score_gemma":0.000366182,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006560184,"about_ca_topic_score_gemma":0.006599546,"domain_scores_codex":[0.9997638,0.0000383535,0.00001620685,0.00006731184,0.00006000455,0.00005437632],"domain_scores_gemma":[0.9997377,0.00008636138,0.00003546766,0.00001851276,0.0000890018,0.00003288482],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001062605,0.0004574924,0.4644772,0.0002179871,0.0002630265,0.0005446129,0.0006068872,0.05740852,0.02621407,0.0013991,0.004510683,0.4428378],"study_design_scores_gemma":[0.00003721718,0.0002303994,0.2664284,0.00003595521,0.0001042782,0.0002939363,0.000633569,0.7241548,0.005510668,0.001246731,0.001276625,0.00004754229],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9195516,0.0004084865,0.07642233,0.0002452668,0.00005257525,0.00009703085,0.0005905358,0.0004288119,0.002203381],"genre_scores_gemma":[0.9813541,0.0001060708,0.01671432,0.00006396519,0.00001822354,0.00007449737,0.0007262214,0.00001256455,0.0009298971],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006560184,"threshold_uncertainty_score":0.013044,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01393668517754666,"score_gpt":0.2558032299488874,"score_spread":0.2418665447713407,"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."}}