{"id":"W2922480644","doi":"10.1016/j.actbio.2019.03.012","title":"Bone extracts immunomodulate and enhance the regenerative performance of dicalcium phosphates bioceramics","year":2019,"lang":"en","type":"article","venue":"Acta Biomaterialia","topic":"Bone Tissue Engineering Materials","field":"Engineering","cited_by":45,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University Health Centre; McGill University","funders":"Consejo Nacional de Ciencia y Tecnología; Natural Sciences and Engineering Research Council of Canada; Ministry of Higher Education, Malaysia; King Saud University; Fondation de l’Ordre des dentistes du Québec; Faculty of Dentistry, McGill University; McGill University","keywords":"Bioceramic; Biomaterial; Materials science; In vivo; Extracellular matrix; Bone healing; Biomedical engineering; Calcium; Self-healing hydrogels; Immune system; Cell biology; Bone tissue; Chemistry; Nanotechnology; Immunology; Biology; Anatomy; 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":[0.0001926259,0.0002131027,0.0002964344,0.00004518538,0.00003834346,0.00007741429,0.0001740982,0.00009878363,0.0001392035],"category_scores_gemma":[0.00001064936,0.0001622418,0.00002680423,0.0001107564,0.00007934564,0.0002069936,0.00006601863,0.00005090074,0.00005786349],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002412921,"about_ca_system_score_gemma":0.000008088028,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002901762,"about_ca_topic_score_gemma":7.570968e-7,"domain_scores_codex":[0.9990966,0.00002298463,0.0003337633,0.0001736807,0.000117073,0.0002559208],"domain_scores_gemma":[0.9994574,0.00002619282,0.00007758407,0.0003693411,0.00002883697,0.0000406076],"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":[0.00002839034,0.000008349789,0.0001204793,0.0002064267,0.00004312704,0.000001180955,0.0002719744,0.0003186679,0.998327,0.00008286929,0.0002590743,0.0003324644],"study_design_scores_gemma":[0.0001970953,0.00006730446,0.008002642,0.00008017212,0.00001380401,0.00001251759,0.00001109447,0.005081652,0.9845709,0.00001474192,0.001745837,0.000202264],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9958909,0.001067572,0.00002794151,0.00006830251,0.002418403,0.0002449162,0.0000361954,0.0001708219,0.00007495598],"genre_scores_gemma":[0.9989032,0.0002665781,0.0003979073,0.000009210662,0.00008689566,0.00001532347,0.00001801261,0.00004917841,0.0002537087],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01375612,"threshold_uncertainty_score":0.661603,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00502505716967857,"score_gpt":0.1989110148271166,"score_spread":0.193885957657438,"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."}}