{"id":"W4411779858","doi":"10.18280/ts.420342","title":"Deep Learning Approaches for Lumbar Spine MRI Segmentation and Classification","year":2025,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Medical Imaging and Analysis","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Deep learning; Artificial intelligence; SPINE (molecular biology); Lumbar spine; Segmentation; Computer science; Computer vision; Medicine; Biology; Surgery; Bioinformatics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001634036,0.00007159275,0.00009033809,0.00007176663,0.0000676597,0.00003482026,0.00003637106,0.0000258658,0.00004138955],"category_scores_gemma":[0.00001133671,0.00006978679,0.00003104721,0.00009877784,0.00002043518,0.00005669897,0.000005672037,0.00006379891,0.000002512129],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002581849,"about_ca_system_score_gemma":0.000004189203,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001314383,"about_ca_topic_score_gemma":0.000001478272,"domain_scores_codex":[0.9995357,0.000014951,0.0001465505,0.0001169658,0.00008047125,0.000105301],"domain_scores_gemma":[0.9998728,0.00001954976,0.00001796367,0.00004054731,0.00001403916,0.00003509518],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000006501802,0.00006504079,0.005009097,0.0005449026,0.000287874,6.923764e-7,0.000660609,0.1285076,0.04925609,0.003418377,0.00169745,0.8105457],"study_design_scores_gemma":[0.0003829453,0.00001540891,0.008132456,0.00002365524,0.00007368002,2.329909e-7,0.0003004543,0.9876884,0.001126402,0.0001373312,0.002048705,0.00007036411],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04538691,0.000353378,0.9525449,0.0003754762,0.00004154701,0.0001464443,9.475602e-7,0.0001088421,0.001041507],"genre_scores_gemma":[0.9936042,0.00008133817,0.005773629,0.00005210831,0.00005811077,0.00007476751,0.00006989916,0.000007927392,0.0002780211],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9482173,"threshold_uncertainty_score":0.2845823,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02445681669137034,"score_gpt":0.244091617627958,"score_spread":0.2196348009365877,"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."}}