{"id":"W4405374842","doi":"10.1016/j.iotech.2024.100889","title":"5MO Novel radiologic phenotypes of chaotic tumor angiogenesis associated with poor ICI outcomes in NSCLC","year":2024,"lang":"en","type":"article","venue":"Immuno-Oncology Technology","topic":"Renal cell carcinoma treatment","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"Syöpäsäätiö; Helsingin Yliopisto; Jane ja Aatos Erkon Säätiö; Ida Montinin Säätiö","keywords":"Angiogenesis; Phenotype; Chaotic; Medicine; Oncology; Internal medicine; Cancer research; Computer science; Biology; Genetics; Gene; Artificial intelligence","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":[0.0002898893,0.0002797305,0.0001475325,0.0008139469,0.0002187081,0.0005892161,0.0001906282,0.0003876743,0.002233714],"category_scores_gemma":[0.0006743823,0.000117167,0.0002374075,0.0003826866,0.0002710691,0.0002822643,0.0003449924,0.0003593819,0.0002434354],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003103864,"about_ca_system_score_gemma":0.0001862359,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008293734,"about_ca_topic_score_gemma":0.0008150176,"domain_scores_codex":[0.9999037,0.00001877097,0.000008165267,0.00002289593,0.00001791463,0.00002853412],"domain_scores_gemma":[0.9995661,0.00005683938,0.0002219695,0.00002240032,0.00006098587,0.00007161064],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001418352,0.0001170224,0.8785847,0.0001160854,0.0001195432,0.002651651,0.0001602719,0.0006212666,0.08779264,0.00114883,0.00109915,0.02617049],"study_design_scores_gemma":[0.00003296134,0.0003322176,0.9771593,0.00002297016,0.00009787063,0.005516239,0.0001985067,0.002362169,0.01115274,0.0008963783,0.00221483,0.00001377853],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.995175,0.0006946002,0.0009840442,0.0001979183,0.00001541959,0.00001868778,0.0003266714,0.00003008799,0.002557636],"genre_scores_gemma":[0.9989063,0.0001167003,0.0003603944,0.00003194882,0.00001933845,0.0000109831,0.0002077413,0.000003881095,0.0003428744],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002233714,"threshold_uncertainty_score":0.007472515,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01844260851793054,"score_gpt":0.274020598656686,"score_spread":0.2555779901387555,"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."}}