{"id":"W2910659915","doi":"10.1101/524801","title":"Nanoscopic Stoichiometry and Single-Molecule Counting","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Fluorescence Microscopy Techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Nanoscopic scale; Stoichiometry; Nanotechnology; Microscopy; Benchmarking; Biological system; Computer science; Materials science; Chemistry; Physics; Optics; Biology; Physical chemistry","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003039333,0.0005929655,0.0004820859,0.0002216538,0.0001283532,0.0001838356,0.0005397786,0.0008350177,0.000009076414],"category_scores_gemma":[0.0002442005,0.0006829581,0.0001111217,0.0002533295,0.0002206527,0.00001370419,0.001194054,0.00057148,0.0000140532],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001089763,"about_ca_system_score_gemma":0.0003136713,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001383752,"about_ca_topic_score_gemma":0.000001404748,"domain_scores_codex":[0.9973533,0.00008382904,0.0004172815,0.001309864,0.0002524043,0.0005833316],"domain_scores_gemma":[0.9977577,0.00001803006,0.0003712388,0.0013752,0.000307881,0.0001699297],"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":[0.00002198006,0.00006647422,0.009087182,0.00028584,0.00006740826,0.000009916514,0.000002168856,0.00001290622,0.9900624,0.00004416034,0.0003367388,0.000002882477],"study_design_scores_gemma":[0.0002789292,0.0001574154,0.006009597,0.0003346333,0.00004599948,4.153174e-8,0.000001898783,0.0000479557,0.9858366,0.000001496728,0.006556216,0.0007292235],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9598613,0.005079074,0.03314937,0.00005324806,0.0006640278,0.0007314018,0.0002123469,0.0002263681,0.00002284786],"genre_scores_gemma":[0.9611892,0.0005572403,0.03732279,0.0003204198,0.0003267886,0.0000844039,0.000002319016,0.0001794175,0.0000174641],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006219477,"threshold_uncertainty_score":0.9995621,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00846742300014862,"score_gpt":0.2343172395624839,"score_spread":0.2258498165623352,"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."}}