{"id":"W4415885506","doi":"10.1021/acs.jcim.5c02263","title":"Meta-Analysis and Topological Perturbation in Interactomic Network for Antiopioid Addiction Drug Repurposing","year":2025,"lang":"en","type":"article","venue":"Journal of Chemical Information and Modeling","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"National Natural Science Foundation of China; Michigan State University","keywords":"DrugBank; Drug repositioning; Druggability; Drug discovery; Repurposing; Biological network; Interaction network; Drug; Addiction","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":[0.001776799,0.0006979416,0.0009196251,0.004889977,0.0003933708,0.001105717,0.0005084991,0.0004189482,0.0007188802],"category_scores_gemma":[0.003515006,0.0002393918,0.00223848,0.003185574,0.0003402624,0.0009507263,0.0008319804,0.0005934853,0.0001209935],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006010093,"about_ca_system_score_gemma":0.0007428657,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001923918,"about_ca_topic_score_gemma":0.002457299,"domain_scores_codex":[0.999184,0.000335022,0.00005049642,0.000241863,0.0001316224,0.00005706843],"domain_scores_gemma":[0.998436,0.0009587292,0.0002368319,0.000186707,0.0001204944,0.00006124002],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"meta_analysis","study_design_scores_codex":[0.001107281,0.0004478954,0.2864078,0.00226023,0.009761998,0.001070251,0.0004122146,0.4078168,0.06251699,0.01534625,0.004223403,0.208629],"study_design_scores_gemma":[0.00003206759,0.0002470951,0.06679299,0.0000733644,0.0022507,0.0002858644,0.0002770489,0.8975981,0.005885114,0.02227169,0.004214981,0.00007097896],"study_design_candidate":"meta_analysis","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6258286,0.008831439,0.3530916,0.001220089,0.00009882294,0.0001597956,0.007705853,0.001325425,0.001738252],"genre_scores_gemma":[0.9482163,0.001335607,0.04517868,0.0001146949,0.00004953269,0.0001200472,0.004620558,0.00006635911,0.0002981636],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004889977,"threshold_uncertainty_score":0.009396732,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02402508144087601,"score_gpt":0.2777878671771578,"score_spread":0.2537627857362817,"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."}}