{"id":"W2099699778","doi":"10.1002/jbm.a.32832","title":"Tuning cell adhesion on titanium with osteogenic rosette nanotubes","year":2010,"lang":"en","type":"article","venue":"Journal of Biomedical Materials Research Part A","topic":"Bone Tissue Engineering Materials","field":"Engineering","cited_by":46,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Institute for Nanotechnology; University of Alberta","funders":"National Institute on Aging","keywords":"Materials science; Osteoblast; Titanium; Adhesion; Cell adhesion; Fibroblast; Biophysics; Biochemistry; Chemistry; In vitro; Biology; Composite material; Metallurgy","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":[0.000130424,0.0003177674,0.0001837751,0.0001258443,0.0001005676,0.0002298481,0.000214605,0.0003281995,0.0002796022],"category_scores_gemma":[0.0001883612,0.0001441435,0.0001830103,0.0001136506,0.00010323,0.0001571992,0.0001918852,0.0001813984,0.0001634568],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002126561,"about_ca_system_score_gemma":0.00009927231,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003109827,"about_ca_topic_score_gemma":0.0008134359,"domain_scores_codex":[0.9998487,0.00002068857,0.00001281326,0.00003385792,0.00005712623,0.00002673154],"domain_scores_gemma":[0.9998798,0.00002677454,0.00004018752,0.000009294663,0.00002932089,0.0000146061],"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":[0.000007310245,0.000002748216,0.00004864133,0.000008447657,0.000001599042,0.000007821624,0.000004035638,0.00005553341,0.9995415,0.00001387437,0.000004794153,0.0003038197],"study_design_scores_gemma":[0.00000254058,0.00006661941,0.001047357,0.000002154239,0.00001038903,0.00003100629,0.00001524833,0.00145197,0.9968063,0.00000655369,0.0005556276,0.000004357878],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9968715,0.0004349017,0.001930489,0.0000172782,0.00001387544,0.00001417296,0.00003844854,0.00001876837,0.0006605984],"genre_scores_gemma":[0.9942225,0.000374361,0.004448549,0.00002946349,0.000006620128,0.00002167953,0.00008185685,0.00001139445,0.0008035651],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0003281995,"threshold_uncertainty_score":0.001542926,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0218033093193817,"score_gpt":0.2808677593427456,"score_spread":0.2590644500233639,"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."}}