{"id":"W2976727130","doi":"10.1016/j.colsurfb.2019.110520","title":"Exploring the mechanism behind improved osteointegration of phosphorylated titanium implants with hierarchically structured topography","year":2019,"lang":"en","type":"article","venue":"Colloids and Surfaces B Biointerfaces","topic":"Bone Tissue Engineering Materials","field":"Engineering","cited_by":27,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"National Key Research and Development Program of China; Sichuan University; National Natural Science Foundation of China","keywords":"Osseointegration; Materials science; Titanium; X-ray photoelectron spectroscopy; Biomedical engineering; Surface modification; Implant; Transmission electron microscopy; Scanning electron microscope; Protein adsorption; Nanotechnology; Adhesion; Chemistry; Chemical engineering; Composite material; Medicine; Metallurgy; Surgery; Polymer","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":[0.0001683155,0.0002539216,0.000336774,0.00008756487,0.00005364966,0.0000956162,0.0001839831,0.00006763831,0.00005155661],"category_scores_gemma":[0.000006222036,0.0001645042,0.00004237571,0.0001622191,0.00006417975,0.0002312873,0.00004469321,0.0001587039,0.000005414723],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001832599,"about_ca_system_score_gemma":0.00001230178,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007352624,"about_ca_topic_score_gemma":0.0001040587,"domain_scores_codex":[0.9990538,0.00002710834,0.000290301,0.0002221304,0.0001539996,0.0002526639],"domain_scores_gemma":[0.9995071,0.00006149972,0.00006127669,0.0002617512,0.00004851727,0.00005982225],"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":[0.00009129666,0.000006662619,0.0004404178,0.0001368945,0.0001255101,0.000001254963,0.000970437,0.003240138,0.9935755,0.0002228253,0.00002191119,0.001167172],"study_design_scores_gemma":[0.0006208456,0.0004132275,0.006227634,0.0001542329,0.00003918337,0.00001881313,0.000629516,0.01463627,0.9764362,0.0001506996,0.0003429056,0.0003304827],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9970791,0.0005228179,0.0006972234,0.00003449607,0.0007158099,0.0004615308,0.00005961343,0.0001761785,0.0002532204],"genre_scores_gemma":[0.9976575,0.0001993233,0.001904607,0.000004516883,0.00001772042,0.00001946475,0.00000843894,0.00004323259,0.0001451447],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01713929,"threshold_uncertainty_score":0.6708286,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0100389912323496,"score_gpt":0.1753908451684436,"score_spread":0.165351853936094,"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."}}