{"id":"W4411959249","doi":"10.2196/79966","title":"A conversational agent for providing personalized PrEP support: Protocol for chatbot implementation and evaluation (Preprint)","year":2025,"lang":"en","type":"preprint","venue":"JMIR Research Protocols","topic":"AI in Service Interactions","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Preprint; Protocol (science); Computer science; Chatbot; World Wide Web; Medicine","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":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.007535052,0.0003727516,0.0003916587,0.0006037934,0.0006583172,0.001255183,0.001514295,0.0002999254,0.0003758961],"category_scores_gemma":[0.0005347119,0.0003825219,0.0002339665,0.0003392203,0.0001296535,0.0008006421,0.002636196,0.0007355785,0.00001515084],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001150962,"about_ca_system_score_gemma":0.004161264,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006600234,"about_ca_topic_score_gemma":0.00006133196,"domain_scores_codex":[0.9940774,0.0008610582,0.0009084858,0.001664358,0.001731842,0.000756849],"domain_scores_gemma":[0.993144,0.001202982,0.0005782265,0.00116178,0.003750206,0.0001627898],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.006206117,0.003078155,0.002466233,0.06702848,0.000896856,0.000007534727,0.03146707,0.001357946,0.00418281,0.1813307,0.2357655,0.4662126],"study_design_scores_gemma":[0.0117484,0.001629015,0.0006045764,0.004472692,0.00001938185,0.000007531245,0.0008404622,0.273442,0.007684951,0.06357447,0.6353078,0.0006687279],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"protocol","genre_gemma":"protocol","genre_scores_codex":[0.00002275097,6.026506e-7,0.1645572,0.002911097,0.0000440089,0.8316896,0.0001776678,0.0001440441,0.0004529767],"genre_scores_gemma":[0.0001108239,1.78361e-7,0.04813787,0.0001518055,0.0002216283,0.9500993,0.000205356,0.00002936096,0.001043607],"genre_candidate":"protocol","genre_consensus":"protocol","teacher_disagreement_score":0.4655439,"threshold_uncertainty_score":0.9998627,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4736918761639891,"score_gpt":0.6516450658894858,"score_spread":0.1779531897254967,"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."}}