{"id":"W6913043098","doi":"10.5683/sp3/xaiw2s","title":"Original NMR data files, and .pdf outputs for ITC and SPR assays for: A high-throughput screening approach to discover potential colorectal cancer chemotherapeutics: Repurposing drugs to identify novel disruptors of 14-3-3 proteins","year":2025,"lang":"en","type":"dataset","venue":"Borealis","topic":"14-3-3 protein interactions","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Repurposing; Colorectal cancer; Cancer; Drug repositioning; Drug discovery; Drug","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00032167,0.0004565191,0.0005423997,0.0001443699,0.0002048255,0.0001804271,0.0006595449,0.0004207551,0.000008230661],"category_scores_gemma":[0.0003185913,0.0004580356,0.0001185472,0.000134299,0.0001201646,0.00003284826,0.0009128433,0.0002073235,2.024107e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007048697,"about_ca_system_score_gemma":0.000307772,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01904561,"about_ca_topic_score_gemma":0.004897724,"domain_scores_codex":[0.9974962,0.00004338413,0.0005052912,0.001258051,0.0002658694,0.0004312333],"domain_scores_gemma":[0.9981617,0.00006450763,0.0003264376,0.001045899,0.0002369587,0.0001644365],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0008995289,0.0001722167,0.00002733663,0.000636139,0.0005802442,8.805962e-7,0.00006153216,0.00004360893,0.03736482,0.00005432541,0.957818,0.002341424],"study_design_scores_gemma":[0.001169397,0.0003606677,0.000187155,0.0003617142,0.0004391406,0.0000160493,0.00008371646,0.0001331948,0.0324814,0.00002013317,0.9642341,0.0005133184],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001684057,0.0004236513,0.1096697,0.0002395402,0.0002121262,0.003169572,0.8845619,0.00001052099,0.0000289572],"genre_scores_gemma":[0.001221026,0.000240198,0.0419666,0.0003089365,0.0006669151,0.001475228,0.9537306,0.00005097446,0.0003395498],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.06916868,"threshold_uncertainty_score":0.9997872,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02574868698006796,"score_gpt":0.3393419282998227,"score_spread":0.3135932413197548,"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."}}