{"id":"W2120430290","doi":"10.1002/anie.201506171","title":"Organized Aggregation of Porphyrins in Lipid Bilayers for Third Harmonic Generation Microscopy","year":2015,"lang":"en","type":"article","venue":"Angewandte Chemie International Edition","topic":"Advanced Fluorescence Microscopy Techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; University of Toronto","funders":"Canadian Institutes of Health Research; Terry Fox Research Institute; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China; Princess Margaret Cancer Foundation","keywords":"Second-harmonic generation; Microscopy; Second-harmonic imaging microscopy; Biophysics; Fluorescence microscope; Lipid bilayer; Fluorescence; Nanoparticle; Nanotechnology; Colloidal gold; Chemistry; High harmonic generation; Materials science; Membrane; Optics; Biochemistry; Physics; Biology","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":[0.0001874686,0.0001141665,0.0001114519,0.00008980758,0.0000210346,0.00001613201,0.0001551072,0.0001358036,0.00001035865],"category_scores_gemma":[0.0002656432,0.0001233657,0.00005459174,0.00008953775,0.00005422365,0.00002922975,0.00004188407,0.00006180485,0.000002505294],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000113943,"about_ca_system_score_gemma":0.00009861399,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002067225,"about_ca_topic_score_gemma":0.00003209318,"domain_scores_codex":[0.999193,0.00001363528,0.0002658668,0.0002531,0.0001499649,0.0001244151],"domain_scores_gemma":[0.99924,0.000009796312,0.0001673089,0.0001411555,0.0004003092,0.0000414753],"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":[0.0001600911,0.00006333675,0.0008374303,0.00000936575,0.00001497707,4.096953e-7,0.00006514084,0.00002709182,0.9798225,0.00005251767,0.01867409,0.0002730227],"study_design_scores_gemma":[0.001005457,0.0001444664,0.0001056903,0.00003326066,0.000006746309,0.000003887332,0.00004896797,0.0001355332,0.9901581,0.0003689004,0.007868205,0.0001207223],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7171217,0.0002369885,0.2795518,0.0005672831,0.001175658,0.0005241839,0.0001674337,0.00003948649,0.0006154385],"genre_scores_gemma":[0.9657211,0.0001819723,0.02977113,0.000178337,0.001144459,0.0001059779,0.002660445,0.00002247851,0.0002140885],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2497807,"threshold_uncertainty_score":0.5030707,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02550529165895285,"score_gpt":0.3105001251562873,"score_spread":0.2849948334973345,"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."}}