{"id":"W4415341652","doi":"10.51594/imsrj.v5i8.2074","title":"Counterfeit medicines and market integrity: Strengthening regulatory intelligence through predictive analytics and cross-sector collaboration","year":2025,"lang":"","type":"article","venue":"International Medical Science Research Journal","topic":"Pharmaceutical Quality and Counterfeiting","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Child, Adolescent and Family Mental Health","funders":"","keywords":"Counterfeit Drugs; Counterfeit; Big data; Predictive analytics; Supply chain; Analytics; Corporate governance; Data sharing; Agency (philosophy)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.03330171,0.0009324267,0.0008318473,0.004897944,0.00276261,0.01796781,0.003278035,0.003987562,0.002969348],"category_scores_gemma":[0.05311739,0.0006783278,0.001098095,0.004292903,0.009967958,0.02578041,0.01602398,0.005193069,0.000676493],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004125324,"about_ca_system_score_gemma":0.01170969,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003432475,"about_ca_topic_score_gemma":0.002103542,"domain_scores_codex":[0.9756521,0.0139403,0.001186058,0.003128803,0.00440173,0.001690914],"domain_scores_gemma":[0.9303154,0.0364515,0.0102626,0.01386587,0.006658727,0.002445888],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000147162,0.0004118432,0.0241271,0.0004241839,0.0002337192,0.0006698165,0.004568769,0.07046321,0.002039744,0.65645,0.007088182,0.2333763],"study_design_scores_gemma":[0.00005511261,0.0001626621,0.00497685,0.0008225723,0.0001303217,0.0002346484,0.003877605,0.1573048,0.004060689,0.7686488,0.05960194,0.0001240196],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1372397,0.004310115,0.6463916,0.09030164,0.000426952,0.0005427868,0.0003257662,0.001749254,0.1187121],"genre_scores_gemma":[0.92893,0.001933776,0.06472632,0.002081665,0.0002132019,0.0001327887,0.000219654,0.0001073823,0.001655202],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03330171,"threshold_uncertainty_score":0.1761184,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1503909147647263,"score_gpt":0.5369235231969787,"score_spread":0.3865326084322523,"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."}}