{"id":"W4413141550","doi":"10.1007/s43762-025-00202-z","title":"Correction: Advancing translational human dynamics research: bridging space, mind, and computational urban science in the era of GeoAI","year":2025,"lang":"en","type":"article","venue":"Computational Urban Science","topic":"Health, Environment, Cognitive Aging","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institute on Governance","funders":"","keywords":"Bridging (networking); Space (punctuation); Dynamics (music); Data science; Translational science; Computer science; Cognitive science; Sociology; Psychology; Social science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008407855,0.003506317,0.003979683,0.006426809,0.005596563,0.008385087,0.006944989,0.01723613,0.1308037],"category_scores_gemma":[0.2107932,0.002187249,0.002762773,0.006046112,0.005793959,0.004901078,0.005290176,0.02055587,0.05680646],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005833182,"about_ca_system_score_gemma":0.01348048,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02924965,"about_ca_topic_score_gemma":0.03287065,"domain_scores_codex":[0.9863753,0.002539665,0.002600776,0.00199315,0.005076274,0.001414857],"domain_scores_gemma":[0.8669227,0.03409747,0.006940402,0.009693488,0.07622036,0.006125689],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003602536,0.0000047223,0.00006562054,0.0002234174,0.0000165878,0.00008879365,0.00004681471,0.00003354921,0.00002439347,0.0005846283,0.9960023,0.002873105],"study_design_scores_gemma":[0.0002449494,0.00003644447,0.001855489,0.00121006,0.0001029176,0.0006641917,0.0003798925,0.0006013186,0.0004527066,0.004635174,0.989691,0.0001258381],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"other","genre_scores_codex":[0.00007933516,0.0005250713,0.0006986317,0.0639653,0.9312626,0.00004291922,0.001807011,0.0005931608,0.001025945],"genre_scores_gemma":[0.01403569,0.005805494,0.006240164,0.1989555,0.6629103,0.0008328959,0.003616959,0.002455251,0.1051477],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.1308037,"threshold_uncertainty_score":0.4375821,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02627540378473881,"score_gpt":0.3332815037857899,"score_spread":0.3070061000010511,"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."}}