{"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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002094875,0.0001752078,0.0004811019,0.00007642906,0.0000246739,0.00000248125,0.000161869,0.00008571258,0.001145208],"category_scores_gemma":[0.000243696,0.0001187724,0.00005888153,0.0001189851,0.00008594165,0.00003211208,0.00001833083,0.0001075282,0.000003224538],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001941582,"about_ca_system_score_gemma":0.00004606212,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000194612,"about_ca_topic_score_gemma":0.00004754651,"domain_scores_codex":[0.9987387,0.00003855174,0.0004615386,0.0002372763,0.0003030295,0.0002209183],"domain_scores_gemma":[0.9986132,0.0005065623,0.0003065111,0.0003063968,0.0002030603,0.00006427781],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002827863,0.001285168,0.6579531,0.003615491,0.0004798268,0.000001232706,0.003340306,0.0001708975,0.00933556,0.305748,0.009451079,0.008336606],"study_design_scores_gemma":[0.02235815,0.01320852,0.5317269,0.007948786,0.001072077,0.000002663584,0.00115256,0.008322734,0.004789154,0.4054226,0.002478758,0.00151708],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9925053,0.0001855277,0.002049373,0.001127672,0.0006163963,0.001189513,0.0001007278,0.00003429057,0.00219123],"genre_scores_gemma":[0.9908758,0.00005089324,0.007913034,0.0002865231,0.0001998692,0.0002920999,0.00003940673,0.0000321024,0.0003102451],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1262262,"threshold_uncertainty_score":0.9997679,"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."}}