{"id":"W4380085707","doi":"10.2139/ssrn.4466486","title":"A Discovery Pipeline for Identification and &lt;i&gt;in vivo&lt;/i&gt; Validation of Drugs that Alter T Cell/ Dendritic Cell Interaction","year":2023,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institute of Infection and Immunity","funders":"","keywords":"Identification (biology); Pipeline (software); In vivo; Cell; Computational biology; Computer science; Cell biology; Chemistry; Biology; Biochemistry; Programming language; Genetics","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":[0.001340617,0.001771876,0.00139185,0.002094857,0.000744214,0.002225123,0.001541132,0.001348105,0.01593252],"category_scores_gemma":[0.002677403,0.0007391826,0.002096505,0.001375328,0.0003882154,0.001089087,0.001365296,0.00147929,0.009171919],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001002554,"about_ca_system_score_gemma":0.004342054,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003430158,"about_ca_topic_score_gemma":0.006032595,"domain_scores_codex":[0.9994531,0.00006437107,0.00003690426,0.0001797607,0.0002015472,0.00006423971],"domain_scores_gemma":[0.9992412,0.0002953623,0.00007691683,0.0001466313,0.0001750394,0.00006484778],"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":[0.002303432,0.0008629388,0.009938864,0.002902706,0.0008648015,0.001012142,0.0001937869,0.07294712,0.2021073,0.02316039,0.206336,0.4773705],"study_design_scores_gemma":[0.0008546975,0.0009989798,0.004261084,0.0001286444,0.0005339067,0.0006735696,0.00009243604,0.6330678,0.1749725,0.03028866,0.1539818,0.0001459436],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04421069,0.002834393,0.7356964,0.002921211,0.0004452658,0.001870224,0.06969722,0.1258587,0.01646589],"genre_scores_gemma":[0.2062499,0.002757217,0.657573,0.001631598,0.000162104,0.001866511,0.1072513,0.004343865,0.01816455],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01593252,"threshold_uncertainty_score":0.05329961,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02168653119283246,"score_gpt":0.2988309877011568,"score_spread":0.2771444565083243,"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."}}