{"id":"W2738920053","doi":"10.1007/s10439-017-1887-4","title":"Erratum to: Development of an Electromechanical Grade to Assess Human Knee Articular Cartilage Quality","year":2017,"lang":"en","type":"erratum","venue":"Annals of Biomedical Engineering","topic":"Osteoarthritis Treatment and Mechanisms","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal; Biomomentum (Canada); Polytechnique Montréal; Michelin (Canada)","funders":"","keywords":"Articular cartilage; Quality (philosophy); Knee cartilage; Biomedical engineering; Cartilage; Medicine; Computer science; Osteoarthritis; Anatomy; Physics; Pathology; Alternative medicine","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008944251,0.0004816093,0.001440995,0.0005139568,0.00009418041,0.00002852038,0.0003808751,0.0006805864,0.0000550948],"category_scores_gemma":[0.0005426919,0.0004533639,0.0002901662,0.0002724732,0.000057915,0.00008301501,0.0001887976,0.0006161985,0.0000172031],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000711551,"about_ca_system_score_gemma":0.0004418072,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002106315,"about_ca_topic_score_gemma":0.00003083839,"domain_scores_codex":[0.9963645,0.00003859434,0.001081819,0.0005954684,0.001173118,0.0007465367],"domain_scores_gemma":[0.9973261,0.00004008679,0.0002754795,0.0009179178,0.0002408472,0.001199508],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001043243,0.0008738443,0.000003103111,0.001185731,0.0002763429,0.0002366542,0.0004412039,0.000003958717,0.9496017,0.0004631758,0.0329979,0.01381204],"study_design_scores_gemma":[0.00163769,0.007768193,0.0008490492,0.003597027,0.0002236754,0.00003552979,0.00006164895,0.00009742931,0.8136598,0.0001273015,0.1711194,0.0008232964],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9624134,0.001470357,0.01414017,0.002554295,0.0138065,0.002960322,0.0002480872,0.0004467873,0.001960039],"genre_scores_gemma":[0.9552645,0.00006074482,0.02492583,0.0006224278,0.002101054,0.0002991002,0.002322813,0.0002793309,0.01412418],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1381215,"threshold_uncertainty_score":0.9997918,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08863856025340526,"score_gpt":0.3759703835488625,"score_spread":0.2873318232954573,"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."}}