{"id":"W4409798308","doi":"10.61091/jcmcc127b-369","title":"Optimization of Identification and Intervention Path of Psychological Problems of Secondary School Students in Cultural Education Based on Dijkstra’s Algorithm","year":2025,"lang":"en","type":"article","venue":"Journal of Combinatorial Mathematics and Combinatorial Computing","topic":"Educational Technology and Pedagogy","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Dijkstra's algorithm; Identification (biology); Path (computing); Intervention (counseling); Computer science; Algorithm; Psychology; Mathematics education; Shortest path problem; Theoretical computer science; Programming language; Graph","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":[0.001062662,0.001076124,0.001477392,0.001825258,0.0009461651,0.001587857,0.001845894,0.001805677,0.003432617],"category_scores_gemma":[0.002914612,0.0008144442,0.00132308,0.001288636,0.0007576957,0.001168083,0.0008855167,0.0009614327,0.0002387604],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001656329,"about_ca_system_score_gemma":0.005720987,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06870548,"about_ca_topic_score_gemma":0.03186388,"domain_scores_codex":[0.9994167,0.0001351603,0.00005143246,0.0001378581,0.00009647402,0.0001623114],"domain_scores_gemma":[0.9990569,0.0005035154,0.00007416787,0.00002825027,0.0002652813,0.00007197027],"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":[0.00009078741,0.0001735919,0.004784225,0.000116204,0.00007925517,0.00007887626,0.0001630528,0.9213791,0.0007541237,0.002715177,0.00119383,0.06847174],"study_design_scores_gemma":[0.00003580174,0.00004093275,0.0005376072,0.000006264275,0.00002422009,0.00001294602,0.00005427913,0.9979655,0.0002012814,0.0009044776,0.0002087718,0.000007882363],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1468094,0.0003968515,0.84605,0.0006010756,0.00008231992,0.0003344077,0.0001589334,0.0008749195,0.004692045],"genre_scores_gemma":[0.8218366,0.0002506607,0.1732018,0.000137182,0.0000191851,0.0004904675,0.0003215322,0.00005490945,0.003687524],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.06870548,"threshold_uncertainty_score":0.1366111,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01759500044308555,"score_gpt":0.3411118303081931,"score_spread":0.3235168298651075,"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."}}