{"id":"W2941681265","doi":"10.1016/j.media.2019.04.012","title":"Direct automated quantitative measurement of spine by cascade amplifier regression network with manifold regularization","year":2019,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Medical Imaging and Analysis","field":"Engineering","cited_by":49,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"Science and Technology Planning Project of Guangdong Province; China Scholarship Council; National Natural Science Foundation of China","keywords":"Artificial intelligence; Feature (linguistics); Pattern recognition (psychology); Computer science; Discriminative model; Embedding; Regularization (linguistics); Cascade; Mathematics; Overfitting; Regression; Nonlinear dimensionality reduction; Curse of dimensionality; Dimensionality reduction; Artificial neural network; Statistics; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009429602,0.0002228707,0.0007165482,0.0002339917,0.00004596876,0.0000322824,0.0002309555,0.000127559,0.001104541],"category_scores_gemma":[0.0003217668,0.0001531935,0.0001905471,0.002122057,0.00008756419,0.0001262246,0.00003705337,0.0002192204,0.00004117752],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006494039,"about_ca_system_score_gemma":0.00003891385,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001378872,"about_ca_topic_score_gemma":0.00004146045,"domain_scores_codex":[0.9971028,0.0001290254,0.0004957333,0.000329691,0.001617504,0.0003252524],"domain_scores_gemma":[0.9988739,0.00006440984,0.0001322255,0.0003942974,0.000272453,0.0002627257],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001529836,0.001100229,0.08325728,0.001949065,0.04840779,0.0004498219,0.00132158,0.2250807,0.2715535,0.0007097202,0.3404803,0.02553705],"study_design_scores_gemma":[0.0004935419,0.00004727811,0.002288359,0.0003576061,0.002068538,0.000001986771,0.00005143561,0.9825538,0.01026439,0.00001183068,0.001603652,0.0002576013],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09279086,0.003271163,0.893731,0.0008815054,0.0001829257,0.0002929386,0.00002339325,0.001114392,0.007711831],"genre_scores_gemma":[0.9926673,0.0002423586,0.00574012,0.0001143253,0.00005786424,0.00001221637,0.0002336232,0.00003936739,0.000892897],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8998764,"threshold_uncertainty_score":0.9998086,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007527160090647314,"score_gpt":0.2427483486585076,"score_spread":0.2352211885678603,"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."}}