{"id":"W2492962850","doi":"10.1038/srep30854","title":"Composite alginate gels for tunable cellular microenvironment mechanics","year":2016,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Cellular Mechanics and Interactions","field":"Biochemistry, Genetics and Molecular Biology","cited_by":57,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Division of Materials Research; National Institute of Diabetes and Digestive and Kidney Diseases; Natural Sciences and Engineering Research Council of Canada; National Institutes of Health","keywords":"Self-healing hydrogels; Biopolymer; Biophysics; Chemistry; Stiffness; Matrix (chemical analysis); Cell mechanics; Materials science; Cell; Nanotechnology; Biomedical engineering; Composite material; Biochemistry; Polymer; Cytoskeleton; Biology; Polymer chemistry","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":[0.0005159113,0.000133332,0.0001116242,0.0000518745,0.0002462483,0.00008553104,0.0001259438,0.00008087282,0.0001236251],"category_scores_gemma":[0.00004089586,0.0001019686,0.0001568709,0.00005762556,0.00004792702,0.000008288498,0.0001200392,0.00003195126,0.00003459245],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000343308,"about_ca_system_score_gemma":0.00004609038,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000361979,"about_ca_topic_score_gemma":0.000003309504,"domain_scores_codex":[0.9985536,0.00001913535,0.0002854819,0.0006763449,0.0001620906,0.0003033379],"domain_scores_gemma":[0.9988757,0.000007287296,0.0001647481,0.0007597338,0.00009048855,0.000102025],"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":[0.00001144728,0.00005530611,0.00002893437,0.000007406351,0.00002418825,0.0000159587,0.000007745557,0.00000963667,0.9838253,0.0002581598,0.01458868,0.001167216],"study_design_scores_gemma":[0.0001017087,0.00004871681,0.000003057205,0.00001036936,0.00001073113,0.00003941744,0.0000064058,0.00006799399,0.5704937,0.002693766,0.4264305,0.0000936826],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6075821,0.0006258856,0.3832536,0.0004464162,0.006974377,0.000607194,0.00003249908,0.00002522923,0.000452757],"genre_scores_gemma":[0.9695517,0.00003274327,0.001545445,0.00006649274,0.0001190719,0.00006113564,0.0002028239,0.00002816251,0.0283924],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4133316,"threshold_uncertainty_score":0.4158157,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007604766151194284,"score_gpt":0.2163480226536058,"score_spread":0.2087432565024115,"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."}}