{"id":"W4254792448","doi":"10.22215/etd/2018-13373","title":"Design Optimization of Dental Implants Using Additively Manufactured Lattice Materials","year":2018,"lang":"en","type":"dissertation","venue":"","topic":"Cellular and Composite Structures","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Biocompatible material; Materials science; Implant; Dental implant; Dentistry; Biomedical engineering; Dental prosthesis; Prosthesis; Bone resorption; Resorption; Medicine; Surgery","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":[0.00031606,0.0006265541,0.0003649246,0.0005219156,0.0001725586,0.001132341,0.0004493443,0.0004927886,0.001274182],"category_scores_gemma":[0.0004669478,0.0004141635,0.0004610092,0.0003437295,0.0002365574,0.000377117,0.0003928128,0.0002618129,0.0005947582],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003663528,"about_ca_system_score_gemma":0.000513799,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002452046,"about_ca_topic_score_gemma":0.000646126,"domain_scores_codex":[0.9998028,0.00002441624,0.00001223006,0.00003056411,0.00009744688,0.00003244544],"domain_scores_gemma":[0.9998628,0.00003663089,0.00004064012,0.00001203244,0.00003832775,0.000009444483],"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":[0.0002191955,0.0002646247,0.001167157,0.0004895548,0.00004401359,0.0001316276,0.0001085743,0.4296294,0.441704,0.007154267,0.0007948098,0.1182927],"study_design_scores_gemma":[0.00007803276,0.000954581,0.001105163,0.00006406331,0.00008979058,0.0002393322,0.0001216811,0.7810754,0.1996017,0.002982545,0.01362369,0.00006415422],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4607211,0.003565843,0.5006079,0.0001690981,0.0002135718,0.0002065272,0.0001588665,0.0005842515,0.03377273],"genre_scores_gemma":[0.7895994,0.001281446,0.2036299,0.00005483234,0.000022491,0.0001615985,0.00009446752,0.0001480928,0.005007701],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001274182,"threshold_uncertainty_score":0.004262507,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01207189284834933,"score_gpt":0.2327163102199334,"score_spread":0.2206444173715841,"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."}}