{"id":"W4411718850","doi":"10.2196/67825","title":"Communicating Antimicrobial Resistance on Instagram: Content Analysis of #AntibioticResistance","year":2025,"lang":"en","type":"article","venue":"JMIR Infodemiology","topic":"Antibiotic Use and Resistance","field":"Immunology and Microbiology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Preprint; Resistance (ecology); Antimicrobial; Computer science; World Wide Web; Biology; Microbiology; Ecology","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":[0.0005010032,0.0002706604,0.001069764,0.0005466117,0.000235739,0.000008867524,0.000729327,0.0004934427,0.00006668207],"category_scores_gemma":[0.0002873249,0.0002330099,0.0003548276,0.001070664,0.0009114815,0.00004543162,0.0002478589,0.0005298645,0.0000440002],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006598567,"about_ca_system_score_gemma":0.00009667898,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001270153,"about_ca_topic_score_gemma":0.0005746323,"domain_scores_codex":[0.9975758,0.0004801516,0.0009630637,0.0004634196,0.00004038568,0.0004771345],"domain_scores_gemma":[0.9973952,0.0008188824,0.0005148517,0.001070409,0.0001781715,0.0000224511],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.002281872,0.0008002635,0.335573,0.000406409,0.005859003,0.000008651794,0.0007791542,0.0004727678,0.374375,0.2625681,0.01599307,0.0008827311],"study_design_scores_gemma":[0.003241549,0.0002474089,0.8541259,0.001227576,0.001577816,0.000003553585,0.0007296868,0.0001121737,0.1059659,0.0008393282,0.03119265,0.0007364465],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9743841,0.002353339,0.001275794,0.001271712,0.0004010825,0.0003830488,0.000092589,0.0000978661,0.01974051],"genre_scores_gemma":[0.9922377,0.0002694491,0.0006716035,0.001629975,0.000007503883,0.000009057353,0.0001023693,0.00001067397,0.005061591],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5185528,"threshold_uncertainty_score":0.9501869,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.036709739407722,"score_gpt":0.3106376668944208,"score_spread":0.2739279274866988,"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."}}