{"id":"W4379879292","doi":"10.1182/bloodadvances.2023010722","title":"CNL and aCML are prognostically distinct: a large National Cancer Database analysis","year":2023,"lang":"en","type":"letter","venue":"Blood Advances","topic":"Lung Cancer Treatments and Mutations","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Sierra Oncology; MorphoSys; Astellas Pharma; Galecto; Incyte; Bristol-Myers Squibb; Constellation Pharmaceuticals; CTI Biopharma; Gilead Sciences; Karyopharm Therapeutics; Celgene","keywords":"Oncology; Medicine","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005489155,0.0004511162,0.001470857,0.001194826,0.002225302,0.003249344,0.001237408,0.01348966,0.003169807],"category_scores_gemma":[0.03589802,0.0006806477,0.0008749231,0.002663347,0.001392952,0.002007069,0.001283401,0.01589982,0.002954304],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002483397,"about_ca_system_score_gemma":0.003725974,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009584094,"about_ca_topic_score_gemma":0.02625525,"domain_scores_codex":[0.9956053,0.001426188,0.0008777654,0.0005685482,0.001044703,0.0004775082],"domain_scores_gemma":[0.9680586,0.02170126,0.002339509,0.0009794523,0.003994521,0.002926718],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.00009533205,0.00002932115,0.01669723,0.00006611133,0.00007601157,0.0005487619,0.00009071593,0.00003712409,0.00007838885,0.0003638205,0.9734054,0.00851187],"study_design_scores_gemma":[0.0005889276,0.00028047,0.06755714,0.0009806216,0.0006742246,0.005186113,0.002455253,0.001805445,0.0005885693,0.008776121,0.9108612,0.0002458879],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.003638131,0.00170274,0.0001250454,0.9784127,0.01184005,0.00002017982,0.002080158,0.00003199269,0.002148993],"genre_scores_gemma":[0.01942787,0.001917114,0.0004907914,0.9367099,0.03621061,0.00009052446,0.001019879,0.0000427262,0.004090621],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01348966,"threshold_uncertainty_score":0.02902979,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02160825577376911,"score_gpt":0.3620123949419686,"score_spread":0.3404041391681994,"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."}}