{"id":"W4361190926","doi":"10.1021/acs.nanolett.2c03733","title":"4D Force Detection of Cell Adhesion and Contractility","year":2023,"lang":"en","type":"article","venue":"Nano Letters","topic":"Cellular Mechanics and Interactions","field":"Biochemistry, Genetics and Molecular Biology","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"Division of Advanced Cyberinfrastructure; Division of Mathematical Sciences; Natural Sciences and Engineering Research Council of Canada; Office of Integrative Activities; Stavros Niarchos Foundation; Courant Institute of Mathematical Sciences, New York University; Eidgenössische Technische Hochschule Zürich; York University; Division of Information and Intelligent Systems; Alfred P. Sloan Foundation","keywords":"Contractility; Adhesion; Tractive force; Materials science; Nanotechnology; Population; Mechanical engineering; Composite material; Engineering; Biology","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":[0.00007413857,0.00005217945,0.00005576721,0.00003145713,0.00004879515,0.00000861252,0.0000357684,0.00005347721,0.000006295706],"category_scores_gemma":[0.00001931493,0.00005202734,0.00004249844,0.00005733769,0.00001994139,0.000002897759,0.00003181676,0.00003320622,0.000005410997],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004559229,"about_ca_system_score_gemma":0.000005544334,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002020344,"about_ca_topic_score_gemma":0.00001274034,"domain_scores_codex":[0.999615,0.00001862463,0.00008985902,0.0001383348,0.00005022239,0.00008792526],"domain_scores_gemma":[0.9997766,0.000009890457,0.00004327313,0.0001252118,0.00002183796,0.00002319798],"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":[0.00002551117,0.00001039215,0.00009074388,0.00001110961,0.00000649116,7.54953e-7,0.00001160081,0.000004473549,0.9983352,0.000009081916,0.0003924822,0.001102095],"study_design_scores_gemma":[0.000178249,0.00007238029,0.0008281753,0.000003471643,0.000006909846,0.000003360522,0.00003292807,0.000175356,0.9868243,0.00001465941,0.01180867,0.00005155724],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9964136,0.00006232869,0.00294036,0.0001922953,0.00017465,0.00006760986,0.000006225252,0.000009705353,0.0001331979],"genre_scores_gemma":[0.999334,0.00007413327,0.00005410295,0.0002473093,0.00004994552,0.000005287771,0.00002798304,0.000007296169,0.0001999535],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01151098,"threshold_uncertainty_score":0.2121613,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006580315787978564,"score_gpt":0.218676114174194,"score_spread":0.2120957983862154,"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."}}