{"id":"W2911046968","doi":"10.7150/thno.28376","title":"Highly-Soluble Cyanine J-aggregates Entrapped by Liposomes for <i>In Vivo</i> Optical Imaging around 930 nm","year":2019,"lang":"en","type":"article","venue":"Theranostics","topic":"Photoacoustic and Ultrasonic Imaging","field":"Engineering","cited_by":46,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"National Institute of Biomedical Imaging and Bioengineering; Ciência sem Fronteiras; National Institutes of Health; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Cyanine; Liposome; Chemistry; Fluorescence; Aqueous solution; Absorption (acoustics); In vivo; Fluorescence-lifetime imaging microscopy; Indocyanine green; Biophysics; Photochemistry; Chromatography; Materials science; Organic chemistry; Biochemistry; Optics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001518283,0.0002594885,0.000313985,0.00006880789,0.00003201854,0.00007667871,0.0002113852,0.00007403995,0.00005250447],"category_scores_gemma":[0.00005737768,0.0002588031,0.00007229486,0.0001353907,0.0000510175,0.000159314,0.0000215661,0.0002016378,0.00003054168],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009244994,"about_ca_system_score_gemma":0.00002847988,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002262247,"about_ca_topic_score_gemma":0.000002711934,"domain_scores_codex":[0.9986569,0.00001233877,0.0002957581,0.0002449901,0.0001657163,0.0006242443],"domain_scores_gemma":[0.999064,0.0005198515,0.00003289927,0.0002538081,0.00003621135,0.00009327867],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006946048,0.0001017395,0.003254596,0.0002340814,0.00008718485,0.00001257467,0.0004728725,0.01194898,0.9706057,0.001129772,0.009421825,0.002661162],"study_design_scores_gemma":[0.00377898,0.0000842343,0.0001766617,0.0002626898,0.0001004389,0.00003116608,0.0004301433,0.4911923,0.4337984,0.001181887,0.06807883,0.0008843685],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.923252,0.005894681,0.06009442,0.0005907925,0.002295037,0.001125999,0.0001275807,0.001576346,0.00504307],"genre_scores_gemma":[0.9965041,0.000285609,0.00196202,0.0003179863,0.0001463682,0.00002809069,0.00002248865,0.0001661769,0.0005671519],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5368074,"threshold_uncertainty_score":0.9999864,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003762545921786898,"score_gpt":0.1943034855826335,"score_spread":0.1905409396608466,"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."}}