{"id":"W1536552954","doi":"","title":"A large-scale computational approach to drug repositioning.","year":2006,"lang":"en","type":"article","venue":"PubMed","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada's Michael Smith Genome Sciences Centre","funders":"","keywords":"DrugBank; Docking (animal); Drug discovery; Computational biology; Drug; Protein–ligand docking; Computer science; Chemistry; Virtual screening; Pharmacology; Biology; Biochemistry; Medicine","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":[],"consensus_categories":[],"category_scores_codex":[0.0007991715,0.0001302958,0.0001435371,0.0001738645,0.0001732224,0.0002919617,0.0005545201,0.00002877599,0.000002081411],"category_scores_gemma":[0.00004348065,0.0001369938,0.0000790374,0.0007123981,0.00002195456,0.0004193916,0.0002882582,0.00009498555,0.00003489901],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009970905,"about_ca_system_score_gemma":0.00005013537,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003380484,"about_ca_topic_score_gemma":0.00000525246,"domain_scores_codex":[0.9981503,0.0001526348,0.0002834253,0.0005100284,0.000491145,0.000412453],"domain_scores_gemma":[0.9991499,0.0001937052,0.00007747297,0.0003223372,0.0001188574,0.0001377839],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000007927263,0.0003664146,0.0009062602,0.0000112471,0.00001279056,0.000006200777,0.0006010627,0.7322645,0.00000305763,0.2344008,0.01376446,0.01765531],"study_design_scores_gemma":[0.0003538763,0.000005025609,0.4194379,0.000003427541,0.000004786261,0.00004482161,0.0000243484,0.5043616,0.0001009396,0.07031641,0.005096781,0.0002500004],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03449209,0.0000382245,0.9283482,0.001391798,0.0002410264,0.0004954793,0.000009032505,0.0002273172,0.03475685],"genre_scores_gemma":[0.5872203,9.17791e-8,0.4104396,0.0006431838,0.0001371412,0.0006686586,0.00003075777,0.00000910842,0.0008510898],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5527282,"threshold_uncertainty_score":0.5586446,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01408733536182092,"score_gpt":0.2358862336256728,"score_spread":0.2217988982638519,"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."}}