{"id":"W7135152457","doi":"10.5281/zenodo.18987501","title":"AI-Powered Tools for Enhancing Drug Identification in Tidjani Village Pharmacists, Tanzania","year":2013,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Pharmaceutical Quality and Counterfeiting","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Tanzania; Identification (biology); Health care; Medical prescription; Convolutional neural network; Artificial neural network","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001167813,0.0001396066,0.0001996653,0.0001910405,0.000708563,0.0007677538,0.0003851879,0.00005612366,0.009775981],"category_scores_gemma":[0.001310433,0.0001482712,0.00006635259,0.000410917,0.00008324822,0.0006390398,0.0002739026,0.0003049391,0.005497122],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000210361,"about_ca_system_score_gemma":0.000007069321,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001306535,"about_ca_topic_score_gemma":6.127351e-7,"domain_scores_codex":[0.9981636,0.0002197585,0.0004721182,0.0003973599,0.0003337776,0.000413316],"domain_scores_gemma":[0.9986854,0.00008532023,0.0001102963,0.0003053685,0.0006095308,0.0002040769],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003381241,0.0004129433,0.00001511569,0.0005825337,0.00006786556,0.00002048986,0.002715059,0.000009952308,0.7114312,0.004124451,0.09061497,0.1896673],"study_design_scores_gemma":[0.00341442,0.0002066031,0.001664238,0.0002016175,0.00005831723,0.0001596028,0.001429377,0.004909368,0.07087895,0.001074314,0.915625,0.0003782417],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8505217,0.0003870737,0.03465452,0.0139373,0.0004641157,0.005971822,0.0003926329,0.001791738,0.09187909],"genre_scores_gemma":[0.9957691,0.00006404571,0.0001552122,0.001411607,0.0001667448,6.28213e-7,0.0009067345,0.0005579948,0.0009679277],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.82501,"threshold_uncertainty_score":0.9952772,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06706337286818212,"score_gpt":0.33567229897885,"score_spread":0.2686089261106679,"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."}}