{"id":"W1987610986","doi":"10.1557/jmr.2008.0089","title":"Microstructural and electrochemical characterization of hydroxyapatite-coated Ti6Al4V alloy for medical implants","year":2008,"lang":"en","type":"article","venue":"Journal of materials research/Pratt's guide to venture capital sources","topic":"Bone Tissue Engineering Materials","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research","keywords":"Materials science; Anodizing; Titanium alloy; Layer (electronics); Titanium; Coating; Composite material; Composite number; Alloy; Substrate (aquarium); Chemical engineering; Metallurgy; Aluminium","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001317503,0.000253311,0.0006761929,0.000321156,0.00008983483,0.00009414321,0.0003930401,0.0002622527,0.0002456822],"category_scores_gemma":[0.0006603534,0.0002180417,0.00007938446,0.0001819938,0.0001423918,0.0002396302,0.0001028494,0.0002787573,0.000009683328],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009266816,"about_ca_system_score_gemma":0.00008433313,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001654178,"about_ca_topic_score_gemma":0.000002243398,"domain_scores_codex":[0.9972998,0.0001279217,0.001053929,0.000192405,0.0007963671,0.0005295884],"domain_scores_gemma":[0.9987187,0.0001721523,0.0002086902,0.0001724249,0.0003760153,0.0003520402],"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":[0.0002473863,0.00002296641,0.0000535344,0.0002726094,0.00009471696,0.00004690865,0.0008526852,0.00009027033,0.9960713,0.00001859269,0.00210181,0.0001271761],"study_design_scores_gemma":[0.0007207837,0.0003870213,0.002513099,0.0002047734,0.00001830693,0.0009041759,0.00004292625,0.0001067749,0.9891744,0.00003717309,0.005682073,0.0002084537],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.997671,0.000480438,0.0003707992,0.0002397625,0.0006603604,0.0003765725,0.000141556,0.00005072348,0.000008773167],"genre_scores_gemma":[0.9977384,0.0004070283,0.0008616458,0.0000233696,0.0007517993,0.0000183635,0.0000639448,0.00007208915,0.00006337655],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006896905,"threshold_uncertainty_score":0.8891482,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01232959159879926,"score_gpt":0.2718532881798406,"score_spread":0.2595236965810413,"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."}}