{"id":"W2156399318","doi":"10.1529/biophysj.107.106864","title":"Detection and Correction of Blinking Bias in Image Correlation Transport Measurements of Quantum Dot Tagged Macromolecules","year":2007,"lang":"en","type":"article","venue":"Biophysical Journal","topic":"Quantum Dots Synthesis And Properties","field":"Materials Science","cited_by":32,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University; Université du Québec","funders":"National Institute of General Medical Sciences; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; University of North Carolina; National Science Foundation; National Institutes of Health; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Fluorescence correlation spectroscopy; Digital image correlation; Quantum dot; Diffusion; Fluorescence; Correlation function (quantum field theory); Materials science; Chemistry; Molecular physics; Biological system; Optics; Physics; Optoelectronics","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":[0.001199195,0.00008715526,0.0001991925,0.0001323071,0.00007003431,0.00002086254,0.00006613654,0.00005515516,0.00002367365],"category_scores_gemma":[0.00007903739,0.00006849952,0.00005775531,0.0001455017,0.0001041465,0.0002050568,0.000008683534,0.0001275736,0.0000027756],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003290389,"about_ca_system_score_gemma":0.00002095498,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001286523,"about_ca_topic_score_gemma":0.00004277465,"domain_scores_codex":[0.998848,0.0000983068,0.0004654772,0.000115626,0.0003259043,0.0001467462],"domain_scores_gemma":[0.9994213,0.00006644616,0.0002990075,0.00006149808,0.0001058292,0.00004593439],"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":[0.0003062437,0.00009631777,0.004963833,0.00002325187,0.00000503091,0.000004075696,0.0003102581,0.00007191576,0.9879183,0.00001705039,0.000001157428,0.00628263],"study_design_scores_gemma":[0.0002935632,0.0001728509,0.07391543,0.0001312835,0.0000174594,0.00002238497,0.0001370519,0.00302643,0.9221279,0.0000806792,0.000004745607,0.0000702398],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9878463,0.00004711681,0.01141748,0.00001195032,0.0005089316,0.00006604859,0.000001852311,0.000008013039,0.00009234919],"genre_scores_gemma":[0.9995564,0.00002073643,0.0003317361,0.000004679461,0.00007333859,7.80817e-7,5.167037e-7,0.00000776214,0.00000404143],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06895159,"threshold_uncertainty_score":0.2793329,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04709114076085408,"score_gpt":0.2632766030313798,"score_spread":0.2161854622705257,"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."}}