{"id":"W4391383352","doi":"10.1177/10732748241230869","title":"Adaptive Control of Tumor Growth","year":2024,"lang":"en","type":"article","venue":"Cancer Control","topic":"Mathematical Biology Tumor Growth","field":"Mathematics","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Medicine; Cancer; Disease; Pathology; Internal medicine","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":[0.0003761076,0.0004461982,0.0003785323,0.0003266191,0.000306727,0.001058859,0.0005939768,0.0005425758,0.001956529],"category_scores_gemma":[0.002288878,0.0001957581,0.0004534854,0.0002238505,0.001092359,0.0006918777,0.001004475,0.0007038201,0.0002206579],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001215396,"about_ca_system_score_gemma":0.0006319339,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002514858,"about_ca_topic_score_gemma":0.001262207,"domain_scores_codex":[0.9997682,0.00005736248,0.000006549586,0.0000706776,0.00005808959,0.00003922372],"domain_scores_gemma":[0.9994693,0.0002472028,0.0001392953,0.00005218121,0.00005319457,0.00003886957],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005433883,0.00003146126,0.001307987,0.0000851096,0.00004109035,0.0001459936,0.0001307323,0.6978975,0.02406813,0.2543897,0.001475264,0.02037263],"study_design_scores_gemma":[0.000008531913,0.00003657464,0.0004751504,0.000007426891,0.000007229914,0.00005125493,0.00002204218,0.9557137,0.001423917,0.04079097,0.001452188,0.00001105692],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1530196,0.001361848,0.804842,0.00207484,0.0002064748,0.00006767624,0.0002077852,0.0004291922,0.0377906],"genre_scores_gemma":[0.9811102,0.0005528893,0.01101021,0.00009130214,0.00004080373,0.00005239857,0.00003863971,0.00004126106,0.007062261],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002514858,"threshold_uncertainty_score":0.008818388,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02753988079105226,"score_gpt":0.3001605945823165,"score_spread":0.2726207137912642,"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."}}