{"id":"W3022729230","doi":"10.1038/s41467-020-15975-6","title":"Mega macromolecules as single molecule lubricants for hard and soft surfaces","year":2020,"lang":"en","type":"article","venue":"Nature Communications","topic":"Dendrimers and Hyperbranched Polymers","field":"Materials Science","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia Hospital; University of British Columbia","funders":"National Institute of Arthritis and Musculoskeletal and Skin Diseases; Natural Sciences and Engineering Research Council of Canada; National Institutes of Health; Orionin Tutkimussäätiö; Simon Fraser University; Päivikki ja Sakari Sohlbergin Säätiö; Canadian Institutes of Health Research; National Institute of Biomedical Imaging and Bioengineering; Suomen Kulttuurirahasto; Michael Smith Health Research BC; Canada Foundation for Innovation; Government of Canada","keywords":"Mega-; Polymer; Macromolecule; Materials science; Nanometre; Molecule; Nanotechnology; Particle size; Particle (ecology); Polymer science; Chemistry; Composite material; Physics; Organic chemistry; Biology","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":[0.0001001776,0.0001094412,0.0001566278,0.00002401831,0.0002964325,0.000110944,0.0007022208,0.0001221012,0.00006084314],"category_scores_gemma":[0.0001812085,0.0001043414,0.00004780301,0.0001353377,0.000184381,0.0001115955,0.0002552558,0.0002182194,0.00003345109],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001184634,"about_ca_system_score_gemma":0.00004165255,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003124956,"about_ca_topic_score_gemma":0.00006031795,"domain_scores_codex":[0.9992717,0.00006202857,0.0001449903,0.0002218108,0.0001180481,0.000181455],"domain_scores_gemma":[0.9989674,0.0001798044,0.00007180873,0.0005822997,0.00007502632,0.0001236283],"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":[0.0000231285,0.00005439966,0.0001980435,0.0000142879,0.00001542377,0.000001018462,0.0006390203,0.000004183273,0.9865947,0.004665599,0.006884096,0.0009060844],"study_design_scores_gemma":[0.0007760382,0.0001920703,0.0007744843,0.00002905472,0.00009445406,0.00002128021,0.0005650263,0.001276379,0.715486,0.0005359833,0.2798299,0.0004193616],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8997765,0.04092836,0.0007820437,0.04646611,0.0002924825,0.0005858138,0.0003244933,0.0002364343,0.01060782],"genre_scores_gemma":[0.9828912,0.0001440394,0.01414144,0.002569092,0.00002728481,0.000028909,0.00004030235,0.00001928657,0.0001384354],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2729458,"threshold_uncertainty_score":0.425492,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03481459715071727,"score_gpt":0.2918024265860696,"score_spread":0.2569878294353523,"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."}}