{"id":"W2028692861","doi":"10.1186/2046-1682-4-13","title":"An upper limit for macromolecular crowding effects","year":2011,"lang":"en","type":"article","venue":"BMC Biophysics","topic":"Hydrogels: synthesis, properties, applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":56,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"National Institutes of Health; National Science Foundation","keywords":"Macromolecular crowding; Limit (mathematics); Computer science; Data science; Crowding; Biology; Macromolecule; Mathematics; Neuroscience","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":[],"consensus_categories":[],"category_scores_codex":[0.00009853356,0.0001857305,0.0001442078,0.00002602445,0.000128598,0.00002683504,0.0003167553,0.0001527186,0.000006232705],"category_scores_gemma":[0.00004653046,0.0001795327,0.0001493818,0.00007725041,0.00008324958,0.000007666633,0.00006803303,0.00005133102,0.00004862003],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001244555,"about_ca_system_score_gemma":0.00005831652,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002016503,"about_ca_topic_score_gemma":0.000005860518,"domain_scores_codex":[0.9989935,0.00004572621,0.0001573357,0.0004301867,0.00008309266,0.0002901781],"domain_scores_gemma":[0.9990575,0.00001341944,0.00006660891,0.0006818249,0.00007757348,0.0001031089],"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":[0.00005204371,0.0001661753,0.0004096277,0.00005796112,0.00003951162,6.251719e-7,0.0000780562,0.000005896619,0.9944575,0.0008826281,0.0001423049,0.003707628],"study_design_scores_gemma":[0.0002643034,0.0002709533,0.00081526,0.00001118833,0.00004781571,0.000002615457,0.0000274512,0.0003295949,0.9906607,0.0006877037,0.00661953,0.0002628861],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9105462,0.0002764718,0.08746805,0.00001628578,0.00009316458,0.0005655626,0.00002804511,0.00004770011,0.0009584886],"genre_scores_gemma":[0.9714726,0.00001974767,0.02727681,0.0002989543,0.0002775643,0.0003434228,0.00009400755,0.00006366378,0.0001532066],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06092639,"threshold_uncertainty_score":0.7321132,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02741795178715587,"score_gpt":0.25134699209132,"score_spread":0.2239290403041641,"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."}}