{"id":"W6945153132","doi":"10.25345/c52954","title":"MassIVE MSV000084644 - Phosphoproteome analysis of pediatric acute leukemia patients and matched xenografts","year":2019,"lang":"en","type":"dataset","venue":"UC San Diego","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Acute leukemia; Acute lymphocytic leukemia; Cancer; MEDLINE; Disease","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0003870403,0.001213058,0.002802082,0.003436051,0.000131027,0.0001318906,0.001262362,0.0009984103,0.003245473],"category_scores_gemma":[0.0002130172,0.001168116,0.0008011203,0.004713762,0.0002543392,0.0002999544,0.0009030329,0.0009066495,0.004071273],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007199203,"about_ca_system_score_gemma":0.000384467,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008915804,"about_ca_topic_score_gemma":0.0004998649,"domain_scores_codex":[0.9942068,0.0002391787,0.001377388,0.001572192,0.001588233,0.001016186],"domain_scores_gemma":[0.9941128,0.0002367535,0.002377387,0.002363166,0.0004981472,0.0004117192],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002921594,0.0002563526,0.0248494,0.0003942304,0.008017352,0.00005912162,0.0001214201,0.00006777231,0.00004997203,7.925875e-7,0.965825,0.00006646772],"study_design_scores_gemma":[0.007901584,0.00119261,0.1884265,0.000198883,0.138534,0.000006423577,0.0001935166,0.0002750992,0.0008115434,0.00005014314,0.6576919,0.00471784],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.187955,0.0006263292,0.000001971666,0.000003235085,0.0004596915,0.001236456,0.8095888,0.00007264117,0.00005588697],"genre_scores_gemma":[0.008237002,0.0007167243,0.0001455301,0.00007495259,0.0002609276,0.0001269423,0.989976,0.0002199384,0.0002419445],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.308133,"threshold_uncertainty_score":0.9990769,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01130441614106381,"score_gpt":0.2543070652167176,"score_spread":0.2430026490756538,"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."}}