{"id":"W4310472863","doi":"10.46471/gigabyte.72","title":"PhysiPKPD: A pharmacokinetics and pharmacodynamics module for PhysiCell","year":2022,"lang":"en","type":"article","venue":"Gigabyte","topic":"Mathematical Biology Tumor Growth","field":"Mathematics","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Open source; Pharmacodynamics; In silico; Key (lock); Computer science; Source code; Pharmacokinetics; Code (set theory); Computational biology; Software engineering; Pharmacology; Medicine; Programming language; Biology; Operating system; Software","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":[0.0008195146,0.00116658,0.0009860317,0.0005606242,0.0004727201,0.001239938,0.003039031,0.00178443,0.09143325],"category_scores_gemma":[0.004431013,0.001020656,0.001252392,0.0005150459,0.0004413425,0.00162705,0.002236691,0.002548191,0.03364795],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008418718,"about_ca_system_score_gemma":0.002513427,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003744974,"about_ca_topic_score_gemma":0.003627239,"domain_scores_codex":[0.9996595,0.00005892655,0.00002922232,0.0000521321,0.000162141,0.00003799181],"domain_scores_gemma":[0.9988644,0.0005797847,0.000088658,0.0001451238,0.0002296561,0.00009233685],"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":[0.0004421122,0.0002846111,0.003667127,0.001907483,0.000291858,0.0005859678,0.0002766082,0.1316085,0.01640552,0.05957548,0.6617202,0.1232345],"study_design_scores_gemma":[0.0003750506,0.00008316413,0.001039334,0.0001660237,0.00006872878,0.0004900499,0.00002991734,0.3861548,0.01113893,0.03596102,0.5643845,0.0001085144],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003805572,0.000605974,0.7730389,0.001313954,0.0004095885,0.0003930253,0.03146293,0.1641828,0.02478728],"genre_scores_gemma":[0.09096746,0.002575304,0.6381055,0.002486068,0.0004773693,0.00352142,0.06150496,0.1416619,0.0587001],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.09143325,"threshold_uncertainty_score":0.3058747,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03873704078232713,"score_gpt":0.3282084953522806,"score_spread":0.2894714545699535,"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."}}