{"id":"W2990172114","doi":"10.1101/856443","title":"Combining hypoxia-activated prodrugs and radiotherapy <i>in silico</i> : Impact of treatment scheduling and the intra-tumoural oxygen landscape","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Cancer, Hypoxia, and Metabolism","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Eurostars; Medical Research Council; Canadian Institutes of Health Research; Swansea University","keywords":"Hypoxia (environmental); Prodrug; Radiation therapy; In silico; In vivo; Exploit; Cancer research; Computer science; Medicine; Biology; Pharmacology; Oxygen; Chemistry; Internal medicine; Biochemistry; Genetics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002021892,0.0001795225,0.0003557415,0.00009469801,0.00008328356,0.0003781359,0.0002667127,0.0002558261,0.001007329],"category_scores_gemma":[0.000465318,0.0001397397,0.0003463271,0.0001169785,0.0002498383,0.0001827944,0.0002438159,0.0002914545,0.0001465987],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003884627,"about_ca_system_score_gemma":0.0002890468,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001169034,"about_ca_topic_score_gemma":0.0008857251,"domain_scores_codex":[0.9999124,0.00002149791,0.000004967751,0.00002104165,0.00002375933,0.00001636574],"domain_scores_gemma":[0.9997613,0.0001509606,0.00004087526,0.00001542696,0.0000153886,0.00001606189],"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":[0.0003878197,0.0001829648,0.002426901,0.0003618429,0.0000608114,0.0002230657,0.00007415636,0.6077825,0.377443,0.001962215,0.0004576997,0.008637015],"study_design_scores_gemma":[0.00005346892,0.001232274,0.002525093,0.00001997843,0.00006482265,0.0001375094,0.00005769681,0.7029069,0.2893937,0.001075147,0.002492609,0.00004068104],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9605938,0.001161225,0.03472187,0.0002200759,0.00005923431,0.0000500402,0.0002243309,0.0001095675,0.00285997],"genre_scores_gemma":[0.9950596,0.0003376885,0.003902959,0.00003028084,0.000005342675,0.00002352962,0.00008310853,0.00001300386,0.0005445221],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001169034,"threshold_uncertainty_score":0.003369808,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008188915894806142,"score_gpt":0.2291946645257289,"score_spread":0.2210057486309227,"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."}}