{"id":"W4414933924","doi":"10.1007/s12559-025-10509-y","title":"Longitudinal Prediction of Mental Health Outcomes in Vulnerable Youth using Machine Learning","year":2025,"lang":"en","type":"article","venue":"Cognitive Computation","topic":"Mental Health Research Topics","field":"Psychology","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"Economic and Social Research Council; Universitat de Barcelona; University College London","keywords":"Mental health; Distress; Mental distress; Intervention (counseling); Cohort; Affect (linguistics); Psychological intervention","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006596535,0.00009001228,0.0002124034,0.0003312483,0.0001752738,0.000009861949,0.00003575669,0.0000472277,0.00007586998],"category_scores_gemma":[0.0001222377,0.00009520828,0.00003059735,0.0003425082,0.00005229869,0.00007728698,0.00004361014,0.0003260406,0.000009112929],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002392574,"about_ca_system_score_gemma":0.0001017659,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001569422,"about_ca_topic_score_gemma":0.0001220044,"domain_scores_codex":[0.9983789,0.0006117228,0.0003718904,0.0002240215,0.0001738212,0.0002396658],"domain_scores_gemma":[0.9994583,0.0002141447,0.0001418525,0.00003266948,0.0001047442,0.00004827053],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001995707,0.0002868875,0.9217574,0.0001327589,0.00004696635,0.000002745662,0.003605304,0.0002223157,0.00003866987,0.0001580848,0.00002784709,0.07352143],"study_design_scores_gemma":[0.003010229,0.0004057158,0.9003565,0.0004486051,0.00001345338,0.000002975663,0.005881295,0.08940513,0.0001502705,0.0002290146,0.00002035288,0.00007649001],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9288315,0.0005287661,0.06693142,0.0002310757,0.0004922492,0.0006298737,0.0001317802,0.00003070091,0.002192598],"genre_scores_gemma":[0.9988019,0.00001666375,0.0002829021,0.0001229637,0.00001737359,0.0000132705,0.0003286455,0.000008093662,0.0004081113],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08918282,"threshold_uncertainty_score":0.3882481,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.149562217537559,"score_gpt":0.4712312717533157,"score_spread":0.3216690542157567,"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."}}