{"id":"W3195311165","doi":"10.1126/sciadv.abe6984","title":"Quantification of fast molecular adhesion by fluorescence footprinting","year":2021,"lang":"en","type":"article","venue":"Science Advances","topic":"Force Microscopy Techniques and Applications","field":"Physics and Astronomy","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia, Okanagan Campus","funders":"Natural Sciences and Engineering Research Council of Canada; Michael Smith Health Research BC; Canada Foundation for Innovation","keywords":"Footprinting; Adhesion; DNA; Cell adhesion molecule; Cell adhesion; Fluorescence; Biophysics; DNA footprinting; Measure (data warehouse); Chemistry; Nanotechnology; Computational biology; Biology; Materials science; Computer science; Cell biology; Gene; Biochemistry; Base sequence; Physics; DNA-binding protein; Data mining; Transcription factor","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":[0.0005723501,0.0007393595,0.0004406657,0.0006126962,0.00036454,0.0006012798,0.0006776213,0.000684202,0.002343293],"category_scores_gemma":[0.0008012425,0.0002385528,0.0002533408,0.0004651785,0.0004238611,0.0005195294,0.0004899577,0.001093818,0.0007203773],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004244065,"about_ca_system_score_gemma":0.0002800699,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001156789,"about_ca_topic_score_gemma":0.001258859,"domain_scores_codex":[0.9994001,0.0000619538,0.00002283298,0.0002068478,0.0002034014,0.0001048058],"domain_scores_gemma":[0.9991743,0.000407035,0.0001288166,0.00008499101,0.0001307049,0.00007425105],"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":[0.00002859625,0.00003006941,0.0003201906,0.00003223824,0.000006388705,0.00001648933,0.0000336581,0.0002021162,0.9957258,0.0001646583,0.00005709547,0.003382786],"study_design_scores_gemma":[0.000003813498,0.0001109608,0.003147805,0.000004984742,0.000008058922,0.00003038541,0.00003238195,0.007142826,0.9884453,0.0001302576,0.0009308417,0.00001252532],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8001502,0.001209278,0.1936905,0.000153367,0.000077828,0.0001509564,0.0008745181,0.0009314224,0.002761988],"genre_scores_gemma":[0.902684,0.001235382,0.09140877,0.0001497097,0.00002928473,0.0004606561,0.0007262682,0.0001001059,0.003205813],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002343293,"threshold_uncertainty_score":0.007839084,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00765033132626402,"score_gpt":0.298977862403235,"score_spread":0.291327531076971,"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."}}