{"id":"W4409605121","doi":"10.61091/jcmcc127b-315","title":"A Study on the Construction of a Predictive Model for Physical Education Teachers’ Professional Development Trajectories Supported by ARIMA Algorithm Driven by Physical Education Reforms","year":2025,"lang":"en","type":"article","venue":"Journal of Combinatorial Mathematics and Combinatorial Computing","topic":"Diverse Approaches in Healthcare and Education Studies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Autoregressive integrated moving average; Physical education; Mathematics education; Professional development; Psychology; Computer science; Algorithm; Machine learning; Pedagogy; Time series","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":[0.002156541,0.0006366664,0.0005558493,0.0008245929,0.0004983851,0.001048394,0.001024315,0.000689398,0.001846205],"category_scores_gemma":[0.006753883,0.0003610534,0.000779049,0.0007129463,0.0002832972,0.001570631,0.0005499846,0.001473123,0.0003111387],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009101389,"about_ca_system_score_gemma":0.001997931,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02826696,"about_ca_topic_score_gemma":0.01535801,"domain_scores_codex":[0.9994465,0.0001864546,0.00003518445,0.0001840796,0.0000904123,0.0000574524],"domain_scores_gemma":[0.9981391,0.0011859,0.000115723,0.00008288431,0.0004173832,0.00005889211],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002219777,0.0002469733,0.03648055,0.0001966272,0.0002148373,0.0002455174,0.0006754256,0.7821521,0.002606434,0.01528583,0.002340817,0.1593329],"study_design_scores_gemma":[0.000004027899,0.00002375698,0.001298046,0.000007077845,0.00001485543,0.00001276018,0.00003338986,0.9972386,0.0002186665,0.0008743644,0.0002685732,0.000005848487],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2371559,0.0004140662,0.7573464,0.0006050799,0.0001082602,0.000139143,0.0002307258,0.0007515823,0.003248838],"genre_scores_gemma":[0.9073996,0.0003440385,0.08920348,0.00007202134,0.00004888633,0.0002094994,0.000418884,0.00005219042,0.002251304],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02826696,"threshold_uncertainty_score":0.05620486,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03163966086289744,"score_gpt":0.3437599671402207,"score_spread":0.3121203062773233,"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."}}