{"id":"W2750846844","doi":"","title":"Upconverting nanoparticles for integration in bioimaging and therapeutic applications.","year":2017,"lang":"en","type":"article","venue":"EspaceINRS Institutional Digital Repository (Institut National de la Recherche Scientifique)","topic":"Nanoparticle-Based Drug Delivery","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Fonds de recherche du Québec – Nature et technologies; Alexander von Humboldt-Stiftung","keywords":"Nanotechnology; Nanoparticle; Computer science; Materials science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002800958,0.0003419617,0.0002178653,0.0002529682,0.0002090512,0.0005527702,0.0004750623,0.0006500029,0.00381701],"category_scores_gemma":[0.0003499852,0.000253951,0.0003446272,0.0002251903,0.0002527926,0.0006746038,0.0004574989,0.0005998433,0.001258433],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006826118,"about_ca_system_score_gemma":0.0002780617,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004438599,"about_ca_topic_score_gemma":0.0008508717,"domain_scores_codex":[0.9998075,0.00002617957,0.00001318764,0.00005638905,0.00007620582,0.00002055487],"domain_scores_gemma":[0.9998982,0.00002552568,0.00002143627,0.00001720928,0.00002969401,0.000007980077],"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":[0.00005169807,0.00002667167,0.0001106362,0.0003365593,0.00001678227,0.0001393005,0.00006443238,0.0005658525,0.9323413,0.006976276,0.002404726,0.05696587],"study_design_scores_gemma":[0.00000784953,0.00008874591,0.0003254403,0.00003117777,0.0000191426,0.0002178383,0.00002147092,0.002859447,0.9252755,0.000774899,0.07036269,0.00001578392],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2672248,0.08135978,0.5262961,0.003898788,0.004159086,0.0007733782,0.001475433,0.003684303,0.1111283],"genre_scores_gemma":[0.640929,0.02605754,0.2416859,0.001212596,0.0002249895,0.0005047743,0.001008713,0.0004426426,0.0879338],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00381701,"threshold_uncertainty_score":0.01276922,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08166081644263921,"score_gpt":0.3382789763053017,"score_spread":0.2566181598626625,"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."}}