{"id":"W2512104978","doi":"10.1002/anie.201606603","title":"Profiling Metal Oxides with Lipids: Magnetic Liposomal Nanoparticles Displaying DNA and Proteins","year":2016,"lang":"en","type":"article","venue":"Angewandte Chemie International Edition","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":54,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Liposome; Calcein; Lipid bilayer; Chemistry; Nanoparticle; Biomolecule; Biosensor; Nanomedicine; Membrane; Chemical engineering; Nanotechnology; Materials science; Biochemistry","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008206019,0.0001284534,0.00009169251,0.00004270097,0.00006321249,0.00003138754,0.0000811409,0.00007247146,0.000006910719],"category_scores_gemma":[0.00007525913,0.00008165764,0.00004242006,0.00004722161,0.0001315953,0.00002416271,0.00005689664,0.0000393348,0.000001531415],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002066109,"about_ca_system_score_gemma":0.00001774966,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004051923,"about_ca_topic_score_gemma":0.00001439181,"domain_scores_codex":[0.9992439,0.00001373549,0.0001418451,0.0002935986,0.0001656365,0.0001413016],"domain_scores_gemma":[0.9996235,0.00001432409,0.00007902332,0.0001191821,0.0001141948,0.00004981238],"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":[0.0001019739,0.00003421722,0.001473634,0.000007066677,0.00004921967,0.00000334368,0.000007219338,2.469598e-7,0.994351,0.00006756174,0.0001287931,0.003775678],"study_design_scores_gemma":[0.0003684717,0.0002267095,0.0005434442,0.00007871363,0.00003110838,0.00004628911,0.00003130102,0.000006799233,0.9964266,0.00017483,0.001912348,0.0001533352],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9936243,0.0001266023,0.004927821,0.0006522064,0.00009269726,0.000120924,0.00004227708,0.00004324842,0.0003699769],"genre_scores_gemma":[0.9939963,0.0001459761,0.004545011,0.0001000148,0.0007365553,0.00003687267,0.0001144259,0.00001453492,0.0003103647],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003622343,"threshold_uncertainty_score":0.3329902,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007831255275267065,"score_gpt":0.23889851369587,"score_spread":0.2310672584206029,"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."}}