{"id":"W4411446314","doi":"10.2196/70525","title":"Sentiment Analysis Using a Large Language Model–Based Approach to Detect Opioids Mixed With Other Substances Via Social Media: Method Development and Validation","year":2025,"lang":"en","type":"article","venue":"JMIR Infodemiology","topic":"Opioid Use Disorder Treatment","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Social media; Euphoriant; Machine learning; Sentiment analysis; Health care; Opioid overdose; Sadness; Computer science; Artificial intelligence; Medicine; Opioid; Psychiatry; Political science; World Wide Web","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004811385,0.000230746,0.0006248051,0.0004453319,0.0001201421,0.00001276213,0.0000732585,0.0001645412,0.00001159393],"category_scores_gemma":[0.00003711545,0.0001786375,0.0000852422,0.0006835401,0.00004143966,0.0000361503,0.00006142699,0.0001301474,0.000001997483],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002185367,"about_ca_system_score_gemma":0.0002115947,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004438992,"about_ca_topic_score_gemma":0.0001292008,"domain_scores_codex":[0.9985033,0.0001911712,0.0003601765,0.0004391047,0.0001748716,0.0003313891],"domain_scores_gemma":[0.999362,0.0001372142,0.0001127916,0.0002235165,0.00007658309,0.00008787889],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003628601,0.002772305,0.6483014,0.001257636,0.01216014,0.00004886387,0.1368073,0.1325352,0.01819658,0.004749897,0.0003344817,0.03920761],"study_design_scores_gemma":[0.009516331,0.0002535588,0.1816197,0.0001373369,0.004815995,0.00001203112,0.007032573,0.7608719,0.0337211,0.0006298959,0.0005180493,0.0008715457],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.525072,0.0001212207,0.4739839,0.0001353001,0.00001615878,0.0004286069,0.000008187409,0.00003774093,0.0001968219],"genre_scores_gemma":[0.6731691,0.000001380834,0.3257811,0.0006269603,0.00001545516,0.0002824833,0.00007987045,0.00001261223,0.00003095319],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6283366,"threshold_uncertainty_score":0.7284626,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02697942514734477,"score_gpt":0.3505482563163053,"score_spread":0.3235688311689606,"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."}}