{"id":"W2908861291","doi":"10.1021/jacs.8b11997","title":"Spying on Neuronal Membrane Potential with Genetically Targetable Voltage Indicators","year":2019,"lang":"en","type":"article","venue":"Journal of the American Chemical Society","topic":"Biochemical and Structural Characterization","field":"Biochemistry, Genetics and Molecular Biology","cited_by":73,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Division of Biological Infrastructure; National Institute of Neurological Disorders and Stroke; National Institute of General Medical Sciences; Natural Sciences and Engineering Research Council of Canada; Agency for Science, Technology and Research; Esther A. and Joseph Klingenstein Fund; Simons Foundation","keywords":"Chemistry; Biophysics; Covalent bond; Fluorescence; Förster resonance energy transfer; Linker; Polyethylene glycol; Conjugated system; Nanotechnology; Combinatorial chemistry; Biochemistry; Polymer; Materials science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001849644,0.0003212169,0.0001496673,0.0001386532,0.00009865908,0.0002516266,0.0003108377,0.0004125162,0.0007137967],"category_scores_gemma":[0.0004894697,0.0001410032,0.0002165783,0.0001300344,0.0002738558,0.0004458364,0.0003492634,0.000531552,0.0002569662],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003147994,"about_ca_system_score_gemma":0.0002045633,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003845512,"about_ca_topic_score_gemma":0.0004861155,"domain_scores_codex":[0.9998839,0.00001762535,0.000006408407,0.00002848532,0.00004412483,0.00001942599],"domain_scores_gemma":[0.9997987,0.00006937385,0.00006448379,0.00001749483,0.00002630542,0.00002364366],"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":[0.00001208165,0.000004027221,0.00004758225,0.00003366373,0.000003664327,0.00002995956,0.00001088067,0.0001156695,0.9974958,0.0002729066,0.00002687895,0.00194668],"study_design_scores_gemma":[0.000003390787,0.00007307937,0.0003349522,0.000003670933,0.000004136352,0.00007953159,0.000005330292,0.00082632,0.9976202,0.00005480052,0.0009919112,0.000002550913],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9343601,0.003597967,0.05782017,0.000257704,0.00007964065,0.00005746464,0.0001309254,0.0002371498,0.003458826],"genre_scores_gemma":[0.961477,0.003610106,0.02995877,0.0001693566,0.00003034213,0.00006945807,0.0002367269,0.00006938624,0.004378853],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007137967,"threshold_uncertainty_score":0.002387881,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002572009878338699,"score_gpt":0.1913635412824626,"score_spread":0.1887915314041239,"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."}}