{"id":"W2006297330","doi":"10.1118/1.1949750","title":"L‐curve analysis of radiotherapy optimization problems","year":2005,"lang":"en","type":"article","venue":"Medical Physics","topic":"Numerical methods in inverse problems","field":"Mathematics","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Research Council Canada; Northwestern University","keywords":"Regularization (linguistics); Mathematics; Curvature; Applied mathematics; Inverse problem; Residual; Curve fitting; Tikhonov regularization; Mathematical optimization; Mathematical analysis; Algorithm; Geometry; Computer science; Statistics","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008415831,0.000141658,0.0005330772,0.0000948606,0.00003444757,0.000009417073,0.0002828768,0.0001269174,0.001469067],"category_scores_gemma":[0.0009011905,0.0001180851,0.0002238546,0.001272581,0.0001737266,0.00009563755,0.00004645567,0.0002121119,0.000007602462],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006723087,"about_ca_system_score_gemma":0.00005011443,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001368065,"about_ca_topic_score_gemma":0.000004745166,"domain_scores_codex":[0.9981058,0.0001612359,0.0005006285,0.0002241789,0.0007920369,0.0002160858],"domain_scores_gemma":[0.9983537,0.0007771786,0.0002444948,0.0003736368,0.0001005983,0.0001503439],"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":[0.00005440184,0.002813155,0.004598554,0.0004663737,0.005509425,0.000005157724,0.003553305,0.3318844,0.0007237159,0.06879881,0.007664431,0.5739283],"study_design_scores_gemma":[0.0007348252,0.00008381577,0.0000576776,0.0000712944,0.0008426837,0.000001106194,0.00001763467,0.8807282,0.003261655,0.1105147,0.003402272,0.000284036],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001987768,0.00007701429,0.9947627,0.0006923576,0.00009094329,0.0001667037,0.000006272968,0.00008039671,0.002135814],"genre_scores_gemma":[0.0776012,0.0001641017,0.9208944,0.000571596,0.0004459245,0.00003240962,0.00001802864,0.00004637296,0.0002259231],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.5736443,"threshold_uncertainty_score":0.9994437,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05918871230081608,"score_gpt":0.3633109682753447,"score_spread":0.3041222559745286,"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."}}