{"id":"W6958336340","doi":"10.6084/m9.figshare.26617816.v1","title":"Additional file 2 of Cytogenetic profile of 1791 adult acute myeloid leukemia in India","year":2024,"lang":"en","type":"article","venue":"Figshare","topic":"Acute Myeloid Leukemia Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre","funders":"","keywords":"Myeloid leukemia; Leukemia; Disease; Mutation; Myeloid","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007499994,0.0005361598,0.0008513502,0.002424764,0.0006158765,0.001026568,0.001207136,0.0006335081,0.7816553],"category_scores_gemma":[0.01658862,0.0003245559,0.0005166469,0.005537606,0.0001680572,0.0009133944,0.0007292548,0.000619668,0.09894259],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008648122,"about_ca_system_score_gemma":0.001504098,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01315245,"about_ca_topic_score_gemma":0.01683239,"domain_scores_codex":[0.9994784,0.00007050056,0.000126471,0.0001289974,0.0001128934,0.00008281763],"domain_scores_gemma":[0.9903399,0.005731049,0.001034248,0.0007067117,0.001806927,0.0003811533],"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":[0.0002356126,0.00005122217,0.005362944,0.001622256,0.00003628761,0.0001251485,0.00008984192,0.0002153375,0.0001114613,0.0005015809,0.9803827,0.01126564],"study_design_scores_gemma":[0.002228585,0.0002372262,0.1154383,0.004112,0.0002470046,0.001342166,0.001004476,0.0007832114,0.0009238708,0.005884753,0.8676726,0.0001257194],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.0003162625,0.00002167235,0.00006712933,0.000087169,0.00001290139,0.00003708779,0.9982565,0.00009425682,0.001107098],"genre_scores_gemma":[0.01264227,0.0002181397,0.0009737181,0.0004324717,0.00008230933,0.0006946271,0.9741738,0.0002325702,0.01054994],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.7816553,"threshold_uncertainty_score":0.3114423,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01975040268378538,"score_gpt":0.283099212874789,"score_spread":0.2633488101910036,"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."}}