{"id":"W4387269182","doi":"10.1002/brx2.33","title":"Understanding the heterogeneous immune repertoire of brain metastases for designing next‐gen therapeutics","year":2023,"lang":"en","type":"article","venue":"Brain‐X","topic":"Brain Metastases and Treatment","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; University of Toronto; University Health Network","funders":"Canadian Institutes of Health Research","keywords":"Immune system; Tumor microenvironment; Brain tumor; Immunotherapy; Infiltration (HVAC); Medicine; Circulating tumor cell; Neuroscience; Biology; Cancer; Pathology; Metastasis; Immunology; Internal medicine","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009361018,0.0002017637,0.0003925628,0.0001222893,0.0002622311,0.00003506067,0.0001355508,0.00006503829,0.00004823627],"category_scores_gemma":[0.0002751091,0.0001283204,0.0003370591,0.0003899763,0.0001325948,0.00005182263,0.00005485893,0.00009436076,0.00001192846],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009409858,"about_ca_system_score_gemma":0.00009329684,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002724396,"about_ca_topic_score_gemma":0.00001071941,"domain_scores_codex":[0.9985687,0.0001446129,0.0003721273,0.0002729738,0.000267734,0.0003738828],"domain_scores_gemma":[0.9974855,0.001737041,0.0001478318,0.0004953833,0.00006114099,0.00007316217],"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":[0.004418133,0.001871527,0.003258197,0.002157773,0.01791626,0.001420336,0.01608449,0.005285157,0.558697,0.05824259,0.08795927,0.2426893],"study_design_scores_gemma":[0.03785231,0.01242805,0.007687591,0.00200251,0.008381024,0.002149474,0.04435902,0.03580374,0.4480454,0.04999195,0.3486452,0.002653783],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5708404,0.01881575,0.2377456,0.158678,0.001249694,0.00914389,0.0007174823,0.001088707,0.00172046],"genre_scores_gemma":[0.9932891,0.0001167341,0.002671476,0.002583908,0.0001016084,0.0001016634,0.0001390872,0.0000612797,0.0009351168],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4224487,"threshold_uncertainty_score":0.5232753,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2390280391217149,"score_gpt":0.3473987038545709,"score_spread":0.1083706647328559,"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."}}