{"id":"W2975634404","doi":"10.1002/cam4.2571","title":"Optimal frequency of scans for patients on cancer therapies: A population kinetics assessment","year":2019,"lang":"en","type":"article","venue":"Cancer Medicine","topic":"Mathematical Biology Tumor Growth","field":"Mathematics","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Medicine; Nuclear medicine; Regimen; Population; Half-life; Residual; Progression-free survival; Internal medicine; Surgery; Chemotherapy; Mathematics; Pharmacokinetics; Algorithm","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":[0.006503647,0.0004215281,0.0008102445,0.001278422,0.000310284,0.001104287,0.0005326863,0.0007568774,0.001211753],"category_scores_gemma":[0.01658154,0.0002165787,0.0005908782,0.0006702793,0.0003772421,0.001100236,0.0007309532,0.0005445023,0.0003368667],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007774237,"about_ca_system_score_gemma":0.0006768294,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008225827,"about_ca_topic_score_gemma":0.0006388774,"domain_scores_codex":[0.9978548,0.001231087,0.0001283241,0.0003719256,0.0003104301,0.0001033341],"domain_scores_gemma":[0.9899111,0.006629789,0.001748423,0.0006799022,0.0007303633,0.0003004743],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.005002714,0.0006031542,0.8228021,0.0001475531,0.0003264722,0.000328565,0.0004759186,0.05210521,0.008042877,0.001854735,0.001625543,0.1066852],"study_design_scores_gemma":[0.0004445494,0.008937577,0.5889198,0.0001029411,0.0006468767,0.002662539,0.00110926,0.3617956,0.01769476,0.01032944,0.007178347,0.0001782809],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9567757,0.0006333499,0.03909688,0.0003148007,0.00000976856,0.000279228,0.0006441915,0.0002640752,0.001982035],"genre_scores_gemma":[0.9886459,0.0001113051,0.01023293,0.00006764958,0.0000142575,0.0002392054,0.000421969,0.00004049902,0.000226273],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006503647,"threshold_uncertainty_score":0.03439498,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03931876241861627,"score_gpt":0.3796850074846246,"score_spread":0.3403662450660083,"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."}}