{"id":"W4383561840","doi":"10.2196/47798","title":"Assessing Vulnerability to Surges in Suicide-Related Tweets Using Japan Census Data: Case-Only Study","year":2023,"lang":"en","type":"article","venue":"JMIR Formative Research","topic":"Mental Health via Writing","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Japan Society for the Promotion of Science","keywords":"Social media; Vulnerability (computing); Suicide prevention; Poison control; Logistic regression; Odds; Injury prevention; Medicine; Occupational safety and health; Social vulnerability; Demography; Psychology; Medical emergency; Computer security; Psychiatry; Psychological intervention; Political science; Sociology; Computer science","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":[0.002732215,0.000799124,0.0009675459,0.002600046,0.001489861,0.0009878997,0.0009776209,0.0009567509,0.001605919],"category_scores_gemma":[0.009036388,0.00126686,0.002139144,0.002385125,0.000658463,0.001208361,0.001945696,0.001049226,0.0003095215],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001710161,"about_ca_system_score_gemma":0.001873838,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02980881,"about_ca_topic_score_gemma":0.03514102,"domain_scores_codex":[0.9965404,0.001143654,0.0007118275,0.0007502983,0.0004300362,0.0004237363],"domain_scores_gemma":[0.9951185,0.0008561938,0.002095885,0.0008420781,0.000668624,0.0004188062],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001155256,0.0001409504,0.9952574,0.0001176067,0.0003281877,0.001267383,0.0008123286,0.00005403621,0.0001687171,0.00006233092,0.0003081569,0.001367372],"study_design_scores_gemma":[0.00004789327,0.0004482806,0.9849505,0.0001471069,0.001003566,0.00424288,0.005945741,0.001482905,0.0003194628,0.0001800973,0.001166362,0.00006501289],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9976744,0.0003940707,0.0005104408,0.00009725836,0.00001975595,0.0002404121,0.0007295602,0.000004695083,0.0003294981],"genre_scores_gemma":[0.9968634,0.0005060167,0.0009732645,0.00008482453,0.00003678797,0.0003942044,0.0009623036,0.000004985395,0.0001741886],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02980881,"threshold_uncertainty_score":0.05927062,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4885037394972874,"score_gpt":0.6227763125201017,"score_spread":0.1342725730228143,"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."}}