{"id":"W2900174653","doi":"10.1093/neuonc/noy148.1174","title":"CADD-35. THE DEVELOPMENT OF PERSONALIZED CAM AVATAR MODEL TO PREDICT CHEMOTHERAPEUTIC DRUG SENSITIVITY/RESISTANCE OF GLIOMAS","year":2018,"lang":"en","type":"article","venue":"Neuro-Oncology","topic":"Cell Image Analysis Techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre Hospitalier Universitaire de Sherbrooke; Université de Sherbrooke","funders":"","keywords":"In ovo; Medicine; Glioma; Ex vivo; Temozolomide; In vivo; Oncology; Chorioallantoic membrane; Drug; Precision medicine; Personalized medicine; Cancer research; Internal medicine; Pathology; Bioinformatics; Pharmacology; Biology; Embryo; Angiogenesis","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":[],"consensus_categories":[],"category_scores_codex":[0.000510826,0.0001748784,0.0003331954,0.00008160726,0.00007978271,0.000005617866,0.0002883598,0.0001347717,0.00002150557],"category_scores_gemma":[0.0001283408,0.0001447417,0.0001172267,0.0001999291,0.0003732531,0.000003978765,0.0002089815,0.0001018886,0.00000531993],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004499597,"about_ca_system_score_gemma":0.000364229,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001773843,"about_ca_topic_score_gemma":0.001071043,"domain_scores_codex":[0.9985627,0.0002016317,0.0003996171,0.0003947902,0.0001949876,0.0002462851],"domain_scores_gemma":[0.9988208,0.00007566062,0.0002216775,0.0005442454,0.0002708631,0.00006673668],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00026156,0.0001074753,0.0001416449,0.00002031935,0.00009284299,0.000003075288,0.001254627,0.00002094021,0.9893575,0.0000228123,0.006711334,0.002005838],"study_design_scores_gemma":[0.0003326973,0.0002091539,0.00009030159,0.000009722348,0.00005425827,0.0000102277,0.0001079002,0.0007067812,0.8985584,0.00002703166,0.09977687,0.0001166495],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9784947,0.0001832009,0.01615479,0.0004988412,0.00003943839,0.0003571602,0.00001287082,0.00002370152,0.004235264],"genre_scores_gemma":[0.9854982,0.00004808892,0.01199798,0.001783687,0.0000972109,0.00003375016,0.00001954995,0.00002854603,0.0004929893],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09306553,"threshold_uncertainty_score":0.5902395,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01482751470210941,"score_gpt":0.288236127921865,"score_spread":0.2734086132197556,"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."}}