{"id":"W4412005418","doi":"10.26685/urncst.886","title":"Advances in Nanotechnology for Diagnosis, Treatment, and Recovery of Bone Cancer","year":2025,"lang":"en","type":"article","venue":"Undergraduate Research in Natural and Clinical Science and Technology (URNCST) Journal","topic":"Nanoplatforms for cancer theranostics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Nanotechnology; Medicine; Cancer; Materials science; Internal medicine","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":[0.001949541,0.0005200759,0.0005390258,0.002403481,0.0004529225,0.0017962,0.0004291855,0.001424412,0.006333364],"category_scores_gemma":[0.001941863,0.0001980648,0.0007068575,0.001517486,0.0008594151,0.002499386,0.001025573,0.001506971,0.001921337],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008540868,"about_ca_system_score_gemma":0.001474436,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006785936,"about_ca_topic_score_gemma":0.001625695,"domain_scores_codex":[0.9991072,0.0002083853,0.00008420661,0.0000924573,0.0004417403,0.00006597651],"domain_scores_gemma":[0.9978815,0.001257997,0.0002337257,0.00007222388,0.0004756813,0.00007879659],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001270454,0.0001340684,0.001852684,0.00929595,0.00007890784,0.0004345879,0.0003634843,0.001035304,0.03290043,0.02645281,0.03181792,0.8955069],"study_design_scores_gemma":[0.00001693031,0.0003006185,0.00310544,0.003657835,0.00009978299,0.002566705,0.0004652914,0.001016668,0.01752978,0.02240381,0.9487689,0.00006830935],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.006295868,0.9413227,0.01139728,0.01754024,0.001971915,0.00006162532,0.0001617269,0.0001274501,0.02112116],"genre_scores_gemma":[0.0319798,0.9299146,0.02526205,0.00316206,0.001865951,0.0000616625,0.0001438369,0.00003635199,0.007573746],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006333364,"threshold_uncertainty_score":0.02118719,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03335632927864149,"score_gpt":0.400418676655485,"score_spread":0.3670623473768435,"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."}}