{"id":"W2950912678","doi":"10.7150/thno.34157","title":"PMMA-Fe <sub>3</sub> O <sub>4</sub> for internal mechanical support and magnetic thermal ablation of bone tumors","year":2019,"lang":"en","type":"article","venue":"Theranostics","topic":"Bone Tissue Engineering Materials","field":"Engineering","cited_by":76,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"National Science Foundation","keywords":"In vivo; Biomedical engineering; Ablation; Bone metastasis; Materials science; Artificial bone; Ex vivo; Metastasis; Medicine; Cancer; Biology","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":[0.0001286872,0.0003890138,0.0001314864,0.0002006115,0.0001808557,0.0001197365,0.0001696474,0.0003038099,0.001990453],"category_scores_gemma":[0.0001788541,0.0001465998,0.0001081691,0.0001312508,0.0002252094,0.0002329257,0.0001829211,0.0003346778,0.0003611095],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001863896,"about_ca_system_score_gemma":0.0001943767,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007840915,"about_ca_topic_score_gemma":0.001567826,"domain_scores_codex":[0.999934,0.000005263392,0.000003402335,0.00001824016,0.00002478548,0.00001425098],"domain_scores_gemma":[0.9999273,0.00001346462,0.00003061696,0.000008854331,0.000007960409,0.00001181462],"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":[0.00004015414,0.000006668822,0.00006235253,0.00004104522,0.000002908315,0.00002570331,0.0000149605,0.0001166157,0.9973778,0.0002303993,0.0001448774,0.001936595],"study_design_scores_gemma":[0.00001043737,0.00005406282,0.00104035,0.00000509263,0.000007360334,0.0001564416,0.000009328634,0.0008667438,0.9930618,0.0000925103,0.004690708,0.000005182194],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8691519,0.005012909,0.102231,0.0005165539,0.000310906,0.0002697712,0.0007980806,0.001163543,0.02054534],"genre_scores_gemma":[0.9570053,0.0006134612,0.03479826,0.00009297744,0.00001990837,0.0001227142,0.0001815069,0.0001331557,0.007032664],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001990453,"threshold_uncertainty_score":0.006658792,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006315680672744376,"score_gpt":0.1911394825292213,"score_spread":0.1848238018564769,"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."}}