{"id":"W2073070417","doi":"10.1021/la047801q","title":"Automated, High-Resolution Micropipet Aspiration Reveals New Insight into the Physical Properties of Fluid Membranes","year":2005,"lang":"en","type":"article","venue":"Langmuir","topic":"Lipid Membrane Structure and Behavior","field":"Biochemistry, Genetics and Molecular Biology","cited_by":57,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"National Heart, Lung, and Blood Institute","keywords":"Membrane; Instrumentation (computer programming); Subpixel rendering; Pipette; Resolution (logic); Nanotechnology; High resolution; Biological membrane; Tracking (education); Chemistry; Biological system; Biomedical engineering; Computer science; Materials science; Geology; Engineering; Artificial intelligence; Remote sensing; Pixel","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":[0.0006799044,0.0003855038,0.00062071,0.0006534791,0.0004726698,0.0008980151,0.0007892765,0.0005533329,0.0005925013],"category_scores_gemma":[0.001062632,0.0003202436,0.0003153843,0.0004835046,0.000819549,0.001042326,0.0007376524,0.0009029718,0.0006169604],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003368163,"about_ca_system_score_gemma":0.0003506787,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006980537,"about_ca_topic_score_gemma":0.001368686,"domain_scores_codex":[0.9994199,0.00009066384,0.000052018,0.0001051568,0.0002828233,0.00004942643],"domain_scores_gemma":[0.9991222,0.0003556822,0.0001353969,0.0002411509,0.000107267,0.00003829177],"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":[0.00003887177,0.0000293193,0.0005246798,0.000119694,0.00001515944,0.00007111912,0.00005453667,0.000645701,0.9705585,0.0007898296,0.0002041099,0.02694846],"study_design_scores_gemma":[0.00002303237,0.0001320876,0.009759737,0.00001567226,0.00003032799,0.000760592,0.00004314227,0.0136892,0.9646605,0.001996759,0.008820855,0.00006808828],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4089586,0.01431338,0.5694783,0.0008047583,0.0001244842,0.0002006026,0.0007447713,0.002243828,0.003131176],"genre_scores_gemma":[0.6177191,0.01125238,0.3666805,0.0004059258,0.0001651041,0.0002639425,0.001193494,0.0001998223,0.002119739],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0008980151,"threshold_uncertainty_score":0.003595769,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01115644334836653,"score_gpt":0.2380678203772246,"score_spread":0.2269113770288581,"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."}}