{"id":"W4210600167","doi":"10.1002/smll.202106547","title":"High‐Efficiency Capture of Cells by Softening Cell Membrane","year":2022,"lang":"en","type":"article","venue":"Small","topic":"Microfluidic and Bio-sensing Technologies","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute of Aging","funders":"National Natural Science Foundation of China","keywords":"Softening; Materials science; Membrane; Circulating tumor cell; Cell; Substrate (aquarium); Adhesion; Cell membrane; Cell adhesion; Nanotechnology; Cancer cell; Biophysics; Chemistry; Composite material; Cancer; Biology; Metastasis","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002459626,0.0004397375,0.0004053726,0.0003004906,0.0001969749,0.0004869495,0.0003982736,0.0008040369,0.0009980073],"category_scores_gemma":[0.0003506234,0.000211292,0.0003782577,0.0002213837,0.000292354,0.0006220657,0.0006114836,0.0005573943,0.0007027558],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003644021,"about_ca_system_score_gemma":0.0001911415,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003394801,"about_ca_topic_score_gemma":0.0004494508,"domain_scores_codex":[0.9997194,0.00002505701,0.00001657679,0.00007004596,0.0001157653,0.00005317495],"domain_scores_gemma":[0.999831,0.00005113644,0.00004288326,0.00002868418,0.00002940201,0.00001685095],"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":[0.00001310558,0.000009650999,0.00006947234,0.00003981115,0.000003668458,0.00004015391,0.00001554327,0.0002059812,0.9957874,0.000252539,0.0001224384,0.003440163],"study_design_scores_gemma":[0.000008795749,0.00005587659,0.0004466626,0.000004673245,0.000006462567,0.00008625718,0.00001317315,0.004831948,0.992254,0.0001014466,0.002178452,0.0000124002],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8543281,0.005365215,0.1293371,0.0007524043,0.0003368285,0.0001123569,0.000221832,0.0007180502,0.008828282],"genre_scores_gemma":[0.9579944,0.002375574,0.03379174,0.0004133106,0.00006561688,0.000104459,0.0001634995,0.00004607162,0.005045168],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009980073,"threshold_uncertainty_score":0.003338695,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0047979478929034,"score_gpt":0.1463706792236633,"score_spread":0.14157273133076,"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."}}