{"id":"W2054955059","doi":"10.1016/j.jocd.2014.07.004","title":"A Trimodality Comparison of Volumetric Bone Imaging Technologies. Part II: 1-Yr Change, Long-Term Precision, and Least Significant Change","year":2014,"lang":"en","type":"article","venue":"Journal of Clinical Densitometry","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"Hamilton Health Sciences; Osteoporosis Canada; University Health Network; McMaster University","funders":"Canadian Institutes of Health Research","keywords":"Medicine; Term (time); Nuclear medicine","routes":{"ca_aff":true,"ca_fund":true,"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":[0.02450876,0.0009824394,0.001910451,0.004094962,0.0004475746,0.001461483,0.001119721,0.001498317,0.002716396],"category_scores_gemma":[0.0465655,0.0004721176,0.002116522,0.001937787,0.0005764917,0.001682042,0.001340741,0.0009115001,0.000916157],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006934114,"about_ca_system_score_gemma":0.0005036271,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001931391,"about_ca_topic_score_gemma":0.001573353,"domain_scores_codex":[0.9912918,0.004026046,0.0007741889,0.00159953,0.002036993,0.0002713582],"domain_scores_gemma":[0.9447263,0.03830978,0.005409842,0.005886977,0.005082963,0.0005840905],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.08236198,0.001274765,0.6323505,0.001296796,0.02059304,0.0002236653,0.0009818766,0.01232149,0.02200288,0.001019614,0.003618086,0.2219554],"study_design_scores_gemma":[0.0008191429,0.009694615,0.9541568,0.000141171,0.003628694,0.000712345,0.0004402378,0.02228396,0.005300049,0.001110512,0.001549721,0.0001626923],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9727769,0.007219569,0.0144784,0.0001505951,0.0001348707,0.0002109594,0.003451647,0.0001980755,0.001378908],"genre_scores_gemma":[0.989711,0.0005118357,0.005926359,0.00009055562,0.00008842737,0.0001466385,0.002771582,0.00007335391,0.0006804311],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02450876,"threshold_uncertainty_score":0.1296163,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1034588782212236,"score_gpt":0.4335112359296578,"score_spread":0.3300523577084342,"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."}}