{"id":"W4310800030","doi":"10.18280/ts.390527","title":"Non-Invasive Machine Learning-Based Classification of Bone Health","year":2022,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Bone health and osteoporosis research","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Osteoporosis; Dual energy; Bone mineral; Gold standard (test); Medicine; Bone disease; Dual-energy X-ray absorptiometry; Disease; Physical therapy; Machine learning; Artificial intelligence; Radiology; Computer science; Internal medicine","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001657404,0.000960319,0.001178098,0.002280745,0.0003174498,0.00124981,0.001441923,0.001312666,0.003308831],"category_scores_gemma":[0.004137578,0.0002166643,0.0008691591,0.001713212,0.0003242809,0.0007850324,0.0005902717,0.0009261757,0.002233124],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000433807,"about_ca_system_score_gemma":0.0006498357,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002949166,"about_ca_topic_score_gemma":0.003182369,"domain_scores_codex":[0.9991174,0.0001827908,0.00008219032,0.0002640334,0.0002630075,0.00009052254],"domain_scores_gemma":[0.9985262,0.0007527443,0.000134811,0.0001037583,0.000439756,0.00004268328],"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":[0.0004910012,0.0005439481,0.02880157,0.0006224297,0.0002614877,0.0003002097,0.00008601152,0.03334817,0.01084406,0.00175981,0.01028413,0.9126571],"study_design_scores_gemma":[0.00005340786,0.0004650768,0.0257333,0.000198976,0.0001767279,0.0008075724,0.0001302357,0.9495909,0.009005402,0.006109647,0.007667648,0.00006100806],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1473263,0.01383932,0.8146782,0.001557571,0.001121884,0.0005331228,0.004734673,0.003807845,0.01240115],"genre_scores_gemma":[0.8003595,0.005063654,0.1759094,0.0007177311,0.0008355994,0.0004750262,0.005701821,0.0001231404,0.01081407],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003308831,"threshold_uncertainty_score":0.01106912,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0399256240939539,"score_gpt":0.3213307912420283,"score_spread":0.2814051671480744,"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."}}