{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001016407,0.0002119106,0.0001161815,0.0001047983,0.0001293804,0.0002951355,0.0002971735,0.0004006835,0.0008603725],"category_scores_gemma":[0.000152427,0.0001496307,0.0002460268,0.0001030921,0.0002385224,0.000378361,0.0002071635,0.0003667352,0.0001642738],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002320145,"about_ca_system_score_gemma":0.0002200767,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006366986,"about_ca_topic_score_gemma":0.0007082243,"domain_scores_codex":[0.9999102,0.000005619596,0.000003832165,0.00001477424,0.00002828872,0.0000373148],"domain_scores_gemma":[0.9999554,0.00001071472,0.00001521296,0.000005394155,0.000008089227,0.000005106046],"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":[0.00005217037,0.00001737607,0.0001435359,0.00007108438,0.000004827127,0.00008407286,0.00002736582,0.0002595699,0.9968194,0.0007771102,0.00005326442,0.001690233],"study_design_scores_gemma":[0.00001323477,0.00009356515,0.0008506936,0.000002542862,0.00001172956,0.00008621795,0.00003598276,0.004499193,0.9936128,0.0001534817,0.0006333929,0.000007090901],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9937845,0.0006283939,0.003779767,0.0001119186,0.00002921874,0.00002265115,0.00005213743,0.00004718362,0.001544168],"genre_scores_gemma":[0.9975861,0.0001785385,0.001650874,0.00002106578,0.000003602703,0.000007826584,0.00002180411,0.000004722733,0.000525462],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008603725,"threshold_uncertainty_score":0.002878189,"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."}}