{"id":"W2945095433","doi":"10.1101/641084","title":"High-throughput microfluidic micropipette aspiration device to probe time-scale dependent nuclear mechanics in intact cells","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Nuclear Structure and Function","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Nautical Research Society","funders":"Division of Chemical, Bioengineering, Environmental, and Transport Systems; Ligue Contre le Cancer; U.S. Department of Defense; National Science Foundation; National Institutes of Health; Fondation ARC pour la Recherche sur le Cancer","keywords":"Pipette; Lamin; Viscoelasticity; Microfluidics; Nucleus; Materials science; Throughput; Biomedical engineering; Nanotechnology; Biological system; Mechanics; Chemistry; Computer science; Physics; Biology; Cell biology; Engineering; Composite material","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0003435416,0.0005404533,0.0004714932,0.0001980442,0.00008961876,0.000157445,0.0005143951,0.0009038305,0.0000648845],"category_scores_gemma":[0.00004026774,0.0006082685,0.0001394271,0.0002526233,0.00002576413,0.00001646589,0.0007303657,0.0005646904,0.0005623095],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002235764,"about_ca_system_score_gemma":0.0002717037,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001200907,"about_ca_topic_score_gemma":0.00001645445,"domain_scores_codex":[0.9973116,0.0001362757,0.0005147706,0.00127191,0.0002639278,0.0005014996],"domain_scores_gemma":[0.9980348,0.000007919431,0.0002801107,0.001247912,0.0002542917,0.0001750034],"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":[0.0001116304,0.00007772628,0.000242055,0.0001553623,0.00007178953,0.00000967649,0.00001118753,0.0001933277,0.9968514,0.00005306163,0.002214091,0.000008731912],"study_design_scores_gemma":[0.0005187767,0.0002739664,0.002628437,0.0001458914,0.00006679334,5.961772e-8,0.000003240006,0.0001040974,0.9630954,0.000002459537,0.03245077,0.0007101608],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9896577,0.0006261159,0.00632558,0.0001727386,0.001770831,0.001195105,0.0001529967,0.00008999058,0.000008965532],"genre_scores_gemma":[0.9903572,0.0002283509,0.007075574,0.001381259,0.0006633184,0.00005578872,0.0000053658,0.000203791,0.0000293271],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03375601,"threshold_uncertainty_score":0.9996369,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005464859308743816,"score_gpt":0.1898559609673771,"score_spread":0.1843911016586333,"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."}}