{"id":"W4396779536","doi":"10.1016/j.jconrel.2024.05.004","title":"Image-based predictive modelling frameworks for personalised drug delivery in cancer therapy","year":2024,"lang":"en","type":"article","venue":"Journal of Controlled Release","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Science and Engineering Research Board","keywords":"Drug delivery; Computer science; Modalities; Risk analysis (engineering); Medical physics; Medicine; Nanotechnology","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":[0.0009436759,0.0009731867,0.001576794,0.000773928,0.0003911272,0.002099452,0.001686021,0.002233456,0.003628237],"category_scores_gemma":[0.002061449,0.0007799854,0.001882807,0.0007716403,0.0008775795,0.001186596,0.001322636,0.001888383,0.0009458019],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001358815,"about_ca_system_score_gemma":0.001282533,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009605527,"about_ca_topic_score_gemma":0.005091244,"domain_scores_codex":[0.9996878,0.0001003779,0.00002405601,0.00004616893,0.0001110893,0.00003051505],"domain_scores_gemma":[0.9993581,0.0004021747,0.00006374651,0.0000337987,0.0001112558,0.00003093127],"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":[0.00002048167,0.00002062009,0.0001994264,0.0001767501,0.0000418261,0.00006665554,0.00004311209,0.9628353,0.001304597,0.02068694,0.001014731,0.01358958],"study_design_scores_gemma":[0.000004962049,0.00001015064,0.00005492674,0.00002832068,0.00001103619,0.00002460041,0.000007391302,0.9893172,0.0002866828,0.006988092,0.003256219,0.00001040738],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004892624,0.005668352,0.9787425,0.0009560712,0.0001564594,0.00007645298,0.0003405048,0.0006897482,0.008477303],"genre_scores_gemma":[0.5543483,0.02618773,0.3950799,0.0009824397,0.000591606,0.001033708,0.001348259,0.0009208885,0.01950726],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009605527,"threshold_uncertainty_score":0.01909924,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01155936443263939,"score_gpt":0.3067027712411702,"score_spread":0.2951434068085308,"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."}}