{"id":"W4391479036","doi":"10.1002/nbm.5101","title":"Characterisation of paediatric brain tumours by their MRS metabolite profiles","year":2024,"lang":"en","type":"article","venue":"NMR in Biomedicine","topic":"Glioma Diagnosis and Treatment","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute of Cancer Research","funders":"Engineering and Physical Sciences Research Council; CHILDREN with CANCER UK; Medical Research Council; Children's Cancer and Leukaemia Group; Great Ormond Street Hospital for Children; Imperial Experimental Cancer Medicine Centre; Brain Tumour Charity; University College London; Little Princess Trust; National Institute for Health and Care Research; Cancer Research UK; Action Medical Research","keywords":"Metabolite; Medulloblastoma; Pilocytic astrocytoma; Astrocytoma; Linear discriminant analysis; In vivo magnetic resonance spectroscopy; Medicine; Magnetic resonance imaging; Voxel; Ependymoma; Nuclear medicine; Pathology; Nuclear magnetic resonance; Glioma; Artificial intelligence; Radiology; Internal medicine; Computer science; Physics; Cancer research","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":[0.0005280116,0.0003820529,0.000589491,0.00140331,0.0001859476,0.0004918393,0.0002505333,0.0003095607,0.0006083733],"category_scores_gemma":[0.002125159,0.0002259321,0.000330489,0.001081093,0.0003861284,0.0003453102,0.0003582788,0.0003660964,0.0002503762],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002923334,"about_ca_system_score_gemma":0.0003512462,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002607464,"about_ca_topic_score_gemma":0.002487481,"domain_scores_codex":[0.9996166,0.00006076931,0.00004664217,0.00009543265,0.0001269351,0.00005358568],"domain_scores_gemma":[0.9992668,0.0001510865,0.000285715,0.00004167868,0.0001977633,0.00005690457],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001609939,0.00006324954,0.7734988,0.0005447812,0.0002169351,0.004658843,0.001003752,0.002736996,0.1531727,0.0003581202,0.0006097735,0.06152618],"study_design_scores_gemma":[0.00001410011,0.0003322811,0.9704882,0.0000340986,0.00007915433,0.007343286,0.0003453012,0.00175576,0.01772024,0.0002280046,0.001638249,0.00002127849],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9938421,0.001524008,0.00293849,0.00003155907,0.000006987148,0.00004132276,0.001043725,0.00003131942,0.0005404456],"genre_scores_gemma":[0.9895521,0.001829559,0.006389339,0.00002939074,0.00001193449,0.00007107939,0.001755361,0.00003152405,0.0003298522],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002607464,"threshold_uncertainty_score":0.005184591,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01147049526295999,"score_gpt":0.2740441929618519,"score_spread":0.2625736976988919,"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."}}