{"id":"W4385798523","doi":"10.1002/jmri.28952","title":"Editorial for “Assessment of Hidden Blood Loss in Spinal Metastasis Surgery: A Comprehensive Approach with <scp>MRI</scp>‐Based Radiomics Models”","year":2023,"lang":"en","type":"letter","venue":"Journal of Magnetic Resonance Imaging","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; Hamilton Health Sciences; Juravinski Hospital; Juravinski Cancer Centre","funders":"","keywords":"Radiomics; Medicine; Spinal surgery; Metastasis; Magnetic resonance imaging; Radiology; Blood loss; Brain metastasis; Surgery; Internal medicine; Cancer","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":[0.004561223,0.001585936,0.002240297,0.001180645,0.002755671,0.004223067,0.002499936,0.03520693,0.006419365],"category_scores_gemma":[0.02970157,0.001084971,0.001944871,0.0006197126,0.002286441,0.002567139,0.001033289,0.03386531,0.01015701],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002697533,"about_ca_system_score_gemma":0.002172787,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002259629,"about_ca_topic_score_gemma":0.004302342,"domain_scores_codex":[0.9968934,0.0007191211,0.000567156,0.0004187074,0.001149436,0.000252262],"domain_scores_gemma":[0.9846851,0.009193753,0.0008980184,0.0003879654,0.003566911,0.001268257],"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":[0.00003663169,0.00001334251,0.00008053269,0.000048462,0.00001292091,0.0004632167,0.00001698427,0.00002492893,0.00005865245,0.000401023,0.9962744,0.002568932],"study_design_scores_gemma":[0.0001929169,0.0000754228,0.00102027,0.0004713723,0.00008149956,0.001761102,0.0001154024,0.0007409047,0.0002958876,0.004592825,0.9905939,0.00005858365],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"editorial","genre_scores_codex":[0.000261197,0.002040858,0.0004182311,0.6099721,0.3842615,0.00006109582,0.0002218664,0.0001441508,0.002619062],"genre_scores_gemma":[0.001761865,0.001372348,0.0003433694,0.4810858,0.507663,0.00007830718,0.0000698939,0.00005210774,0.007573307],"genre_candidate":"editorial","genre_consensus":null,"teacher_disagreement_score":0.03520693,"threshold_uncertainty_score":0.0241223,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02742125829218028,"score_gpt":0.2992684089001247,"score_spread":0.2718471506079444,"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."}}