{"id":"W7114920599","doi":"10.17169/refubium-49956","title":"From fragments to follow-ups: rapid hit expansion by making use of EU-OPENSCREEN resources","year":2025,"lang":"en","type":"article","venue":"Refubium (Universitätsbibliothek der Freien Universität Berlin)","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Deutsche Forschungsgemeinschaft; Horizon 2020 Framework Programme; CancerCare Manitoba Foundation; Austrian Science Fund; Philipps-Universität Marburg","keywords":"Fragment (logic); Bottleneck; Identification (biology); Drug discovery; Drug development","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002746702,0.0009508142,0.00146997,0.001704245,0.000473359,0.00121887,0.001776612,0.0005579338,0.01201594],"category_scores_gemma":[0.005897363,0.0005017723,0.0009258108,0.002162904,0.0003242831,0.00184564,0.003261402,0.001129296,0.00337664],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005829906,"about_ca_system_score_gemma":0.001106646,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001176022,"about_ca_topic_score_gemma":0.001636822,"domain_scores_codex":[0.9984115,0.000548369,0.00008167756,0.0002773479,0.0005151189,0.0001660105],"domain_scores_gemma":[0.9982536,0.0008120323,0.00009998712,0.000496437,0.0001982691,0.0001396231],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.007101712,0.001838935,0.01070499,0.00124444,0.0004080232,0.001019635,0.0005636253,0.06476606,0.1053699,0.01992541,0.05237479,0.7346824],"study_design_scores_gemma":[0.003129081,0.004644118,0.01365806,0.000346544,0.0005260307,0.00196026,0.0006359821,0.4343274,0.2592235,0.04133642,0.2397616,0.0004510532],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6034215,0.006165294,0.2990439,0.001780743,0.000248185,0.00156744,0.01770036,0.03406525,0.03600729],"genre_scores_gemma":[0.6179245,0.002033615,0.3212582,0.0007179861,0.00006716487,0.001627633,0.04774772,0.002871303,0.005751905],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01201594,"threshold_uncertainty_score":0.04019731,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02547464172127895,"score_gpt":0.2755844696635295,"score_spread":0.2501098279422505,"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."}}