{"id":"W2559676511","doi":"10.71781/4681","title":"Improving the use of G-CSF during chemotherapy using physiological mathematical modelling : a quantitative systems pharmacology approach","year":2015,"lang":"en","type":"dissertation","venue":"Papyrus : Institutional Repository (Université de Montréal)","topic":"Mathematical Biology Tumor Growth","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Mitacs; Tsinghua University; McGill University; Université de Montréal; Natural Sciences and Engineering Research Council of Canada; Pfizer","keywords":"Pharmacology; Systems pharmacology; Computational biology; Computer science; Medicine; Biology; Drug","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.0005068224,0.0005441219,0.001019462,0.0002180817,0.001984303,0.00005251146,0.0005626572,0.0005923261,0.00002229364],"category_scores_gemma":[0.0003007289,0.0004150636,0.0003578884,0.0002765066,0.0004504866,0.0002583389,0.0001774661,0.0006790998,0.000007825],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001986458,"about_ca_system_score_gemma":0.000772872,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001620874,"about_ca_topic_score_gemma":0.00002808812,"domain_scores_codex":[0.9969424,0.0004272646,0.0008343837,0.0006234993,0.0006728091,0.0004996175],"domain_scores_gemma":[0.9969416,0.0007420729,0.001093308,0.0004832058,0.0005384104,0.0002014603],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.004860828,0.002294739,0.0001688575,0.008949991,0.003056658,0.0008510563,0.08574624,0.0884046,0.3785731,0.4257744,0.001166233,0.0001533871],"study_design_scores_gemma":[0.00221099,0.0002273473,0.0001361849,0.0007675813,0.001491047,0.001222541,0.03560562,0.9228925,0.01330401,0.02080731,0.0002248298,0.001110093],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9771586,0.001858022,0.01747655,0.00002051499,0.0004775325,0.001061461,0.000049046,0.0001199177,0.001778317],"genre_scores_gemma":[0.9033078,0.0001271831,0.08754874,0.00004022248,0.0003747818,0.0001358032,0.0001844178,0.0001384413,0.008142625],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8344879,"threshold_uncertainty_score":0.9998301,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0719061428088477,"score_gpt":0.2605956955277632,"score_spread":0.1886895527189155,"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."}}