{"id":"W3136835725","doi":"10.1016/j.bone.2021.115917","title":"Osteogenesis imperfecta tooth level phenotype analysis: Cross-sectional study","year":2021,"lang":"en","type":"article","venue":"Bone","topic":"Connective tissue disorders research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":19,"is_retracted":false,"has_abstract":false,"ca_institutions":"Shriners Hospitals for Children - Canada; McGill University","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Child Health and Human Development; National Center for Advancing Translational Sciences; National Institute of Arthritis and Musculoskeletal and Skin Diseases; Rare Diseases Clinical Research Network; National Institutes of Health; National Institute of Dental and Craniofacial Research","keywords":"Dentistry; Medicine; Molar; Pulp (tooth); Dentinogenesis imperfecta; Orthodontics; Dentin","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":[],"consensus_categories":[],"category_scores_codex":[0.0002502157,0.0001224661,0.0001711019,0.00008595028,0.000126304,0.00006626408,0.0001349159,0.0000894164,0.0008037947],"category_scores_gemma":[0.0002581169,0.00012949,0.0001643348,0.000522309,0.00004650423,0.000003152611,0.0002171266,0.0000762761,0.00006698535],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002230096,"about_ca_system_score_gemma":0.0001604321,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001793074,"about_ca_topic_score_gemma":0.001726335,"domain_scores_codex":[0.9986809,0.0001213323,0.0001869397,0.0005163313,0.0002571138,0.0002373501],"domain_scores_gemma":[0.9990573,0.00002042235,0.00003673204,0.0004645614,0.0003500601,0.00007094366],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009220155,0.0002941164,0.6546341,0.000005233613,0.0006965759,0.00002511117,0.00004178355,0.0001240366,0.3428486,0.00001295559,0.0001498624,0.001075387],"study_design_scores_gemma":[0.0007167396,0.0002055397,0.9476235,7.161323e-7,0.00008704532,0.000008359511,0.0002071232,0.00004006851,0.04888988,0.00001395514,0.002048361,0.0001587487],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9962864,0.001545427,0.000581458,0.00004501828,0.0000706346,0.0001715625,0.00006603517,0.000009280646,0.001224213],"genre_scores_gemma":[0.9923529,0.00003073198,0.0001012745,0.00004870241,0.0001320879,0.00004046192,0.0002399034,0.00001851596,0.007035446],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2939588,"threshold_uncertainty_score":0.8800988,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04373457432036226,"score_gpt":0.3500840059647097,"score_spread":0.3063494316443474,"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."}}