{"id":"W4296130880","doi":"10.1101/2022.09.12.507681","title":"PhysiPKPD: A pharmacokinetics and pharmacodynamics module for PhysiCell","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Open source; Key (lock); Pharmacodynamics; In silico; Pharmacokinetics; Computer science; Source code; Code (set theory); R package; Computational biology; Software engineering; Pharmacology; Programming language; Medicine; Chemistry; Biology; Software; Operating system","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":[0.001098661,0.001357986,0.001046087,0.000641391,0.0005626061,0.001491734,0.003037113,0.001589122,0.08188514],"category_scores_gemma":[0.003962148,0.001243135,0.001346841,0.0004933978,0.0005205902,0.001401771,0.002196002,0.002472914,0.03259689],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001017521,"about_ca_system_score_gemma":0.00264373,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003866639,"about_ca_topic_score_gemma":0.003332276,"domain_scores_codex":[0.9996146,0.00006100307,0.00003144281,0.00007615,0.0001741329,0.00004262789],"domain_scores_gemma":[0.9988822,0.0005610923,0.00007846778,0.0001731823,0.000221209,0.00008381801],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007066852,0.0004285208,0.005375389,0.002191326,0.0004823874,0.0008535648,0.0003798804,0.1271925,0.02309574,0.05930734,0.661662,0.1183247],"study_design_scores_gemma":[0.0005295043,0.00008146833,0.001615527,0.0001728388,0.00009282368,0.0005090547,0.00003770283,0.4166652,0.01852627,0.04044319,0.521194,0.0001322986],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.004856443,0.0003678878,0.6751564,0.0007948927,0.0002965447,0.00035832,0.03605643,0.2655641,0.01654908],"genre_scores_gemma":[0.1231849,0.001572219,0.525086,0.002083926,0.0003840532,0.003616332,0.09021214,0.1962064,0.05765397],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.08188514,"threshold_uncertainty_score":0.2739331,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009325799800936134,"score_gpt":0.2363456850998448,"score_spread":0.2270198852989086,"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."}}