{"id":"W2024489667","doi":"10.1038/labinvest.2011.153","title":"Microvascular density as an independent predictor of clinical outcome in renal cell carcinoma: an automated image analysis study","year":2011,"lang":"en","type":"article","venue":"Laboratory Investigation","topic":"Renal cell carcinoma treatment","field":"Medicine","cited_by":59,"is_retracted":false,"has_abstract":false,"ca_institutions":"London Health Sciences Centre; University of Toronto; St. Michael's Hospital","funders":"Canadian Institutes of Health Research","keywords":"Medicine; Renal cell carcinoma; Clear cell renal cell carcinoma; Pathology; CD34; Stage (stratigraphy); Univariate analysis; Proportional hazards model; Vascularity; Carcinoma; Clinical significance; Vascular endothelial growth factor; Oncology; Multivariate analysis; Internal medicine; Biology; VEGF receptors; Stem cell","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":[0.000781689,0.0002831978,0.0004207793,0.001338512,0.0003365566,0.0007072314,0.0003837203,0.0003620572,0.0007227131],"category_scores_gemma":[0.00210641,0.0002079469,0.0003128743,0.0008636008,0.0003805179,0.0004452018,0.000274733,0.0003345821,0.0001335622],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003780003,"about_ca_system_score_gemma":0.0003010225,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002368793,"about_ca_topic_score_gemma":0.001861548,"domain_scores_codex":[0.9995503,0.000166634,0.00002657118,0.00007790044,0.0001332756,0.00004531952],"domain_scores_gemma":[0.998327,0.0007628228,0.0003413153,0.0001490112,0.0003054932,0.0001144166],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003048233,0.0005765688,0.9614387,0.00004668108,0.0002184628,0.0002304243,0.0001345999,0.0006458456,0.008803052,0.00007684182,0.0002174713,0.02456334],"study_design_scores_gemma":[0.00005180372,0.0005701783,0.989758,0.000004245703,0.0001165059,0.0004148349,0.00008759557,0.006892857,0.00185968,0.00007232802,0.000157212,0.00001486822],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9990957,0.0001297456,0.0003881945,0.00000956318,0.00000322913,0.00001459179,0.00005899517,0.000008602,0.0002914795],"genre_scores_gemma":[0.9993499,0.00005149542,0.0004025907,0.000007321806,0.00001095015,0.00001181476,0.00007407042,0.000003039315,0.00008889977],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002368793,"threshold_uncertainty_score":0.004710019,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0601889916748445,"score_gpt":0.336251678588791,"score_spread":0.2760626869139465,"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."}}