{"id":"W2001817833","doi":"10.1117/12.647309","title":"Microvascular geometry and differential permeability in the eye during inflammation revealed with dual channel multiphoton microscopy","year":2006,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Traumatic Brain Injury and Neurovascular Disturbances","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"St. Paul's Hospital; University of British Columbia","funders":"Heart and Stroke Foundation of Canada","keywords":"Fluorescence microscope; Cornea; Biophysics; Microscopy; Plexus; Corneal inflammation; Confocal microscopy; Materials science; Inflammation; Chemistry; IRIS (biosensor); Fluorescence; Optical coherence tomography; Permeability (electromagnetism); Dextran; Differential interference contrast microscopy; Anatomy; Pathology; Ophthalmology; Medicine; Biology; Optics; Cell biology; Membrane","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002818228,0.0002479912,0.0001883187,0.0004756276,0.0002308762,0.000314939,0.0002021726,0.0003914805,0.0007560112],"category_scores_gemma":[0.0002014551,0.0002259271,0.0001863432,0.0002587223,0.0002713328,0.0004582421,0.0003664629,0.0006709587,0.0001335733],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003756692,"about_ca_system_score_gemma":0.0001322606,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008600164,"about_ca_topic_score_gemma":0.000898916,"domain_scores_codex":[0.999856,0.000022646,0.000006443925,0.00003241249,0.00003174211,0.00005082548],"domain_scores_gemma":[0.9998603,0.00003478522,0.00004237003,0.00001409563,0.00002432178,0.00002412657],"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":[0.0001046939,0.00001787555,0.0005997057,0.00003383408,0.000003230391,0.00008695366,0.00003944853,0.0001024919,0.997783,0.0000953865,0.00003415041,0.00109925],"study_design_scores_gemma":[0.00003018509,0.0005957974,0.0830809,0.00002405042,0.00003677624,0.001276013,0.0001874218,0.007702841,0.9050207,0.0003691214,0.001637469,0.00003871712],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9849558,0.001393991,0.01208666,0.00007814099,0.00001597693,0.00003210507,0.0002514422,0.00009381113,0.001092065],"genre_scores_gemma":[0.9821113,0.001417049,0.0146318,0.00006655094,0.00002105157,0.0000920446,0.0002276345,0.00002313033,0.00140949],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008600164,"threshold_uncertainty_score":0.00272572,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007245331073469925,"score_gpt":0.220299722048667,"score_spread":0.213054390975197,"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."}}