{"id":"W1975858564","doi":"10.1016/j.bone.2014.12.023","title":"Unique micro- and nano-scale mineralization pattern of human osteogenesis imperfecta type VI bone","year":2014,"lang":"en","type":"article","venue":"Bone","topic":"Connective tissue disorders research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":64,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University; Montreal Children's Hospital","funders":"Fonds de Recherche du Québec - Santé; Allgemeine Unfallversicherungsanstalt","keywords":"Osteogenesis imperfecta; Osteoid; Mineralization (soil science); Chemistry; Type I collagen; Bone mineral; Population; Matrix gla protein; Collagen, type I, alpha 1; Connective tissue; Biophysics; Extracellular matrix; Internal medicine; Anatomy; Osteoporosis; Endocrinology; Pathology; Biology; Biochemistry; Phosphate; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001434053,0.00008572219,0.0001248587,0.00004513804,0.00004249023,0.000008454168,0.00006219246,0.00008683299,0.00004802941],"category_scores_gemma":[0.00005631789,0.00008731148,0.00002856563,0.00007736034,0.00006167556,0.000002044571,0.00009431754,0.00002945779,0.000004801016],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005307759,"about_ca_system_score_gemma":0.00001678648,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003209486,"about_ca_topic_score_gemma":0.000771497,"domain_scores_codex":[0.9993759,0.00007835434,0.0001277319,0.0002113038,0.0000738221,0.0001329206],"domain_scores_gemma":[0.999556,0.000009331846,0.00004610725,0.0002195039,0.0001268912,0.00004213291],"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":[0.00002733697,0.00003462702,0.02007535,0.00003852073,0.00001271948,4.007361e-7,0.00005453885,0.000001235677,0.9744014,0.00001838747,0.0004325873,0.004902885],"study_design_scores_gemma":[0.0005082784,0.000446759,0.01475782,0.00001263754,0.00001003719,0.000008031039,0.00003535266,0.00003287008,0.9796098,0.00003165115,0.004426411,0.0001202859],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9974808,0.001051041,0.0006914564,0.00008468053,0.0000213953,0.0001343418,0.00001015199,0.000004792719,0.0005214122],"genre_scores_gemma":[0.9983034,0.0001218556,0.00009751767,0.0000551071,0.0000473872,0.0000080268,0.0001330044,0.00001868246,0.001215016],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005317526,"threshold_uncertainty_score":0.3560459,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009180879686259658,"score_gpt":0.2695649602000286,"score_spread":0.260384080513769,"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."}}