{"id":"W4411967886","doi":"10.1016/j.cej.2025.165551","title":"Multi-biomimetic cellulose-based regenerated fibers from scalable wet spinning for ultrahigh-efficiency rate fog harvesting","year":2025,"lang":"en","type":"article","venue":"Chemical Engineering Journal","topic":"Surface Modification and Superhydrophobicity","field":"Materials Science","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of New Brunswick","funders":"National Natural Science Foundation of China","keywords":"Spinning; Cellulose; Regenerated cellulose; Cellulose fiber; Materials science; Chemical engineering; Composite material; Engineering","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":[0.0006285202,0.0002276517,0.0002934067,0.000124598,0.0001906164,0.0002680748,0.0003528701,0.0001369531,0.0001573474],"category_scores_gemma":[0.0008859815,0.0002150687,0.0001253951,0.0003508375,0.00006337342,0.0001366457,0.00003206169,0.0002961435,0.00002621379],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001748592,"about_ca_system_score_gemma":0.0001499441,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003543247,"about_ca_topic_score_gemma":2.956603e-7,"domain_scores_codex":[0.9984686,0.00004136493,0.0004922096,0.0003703766,0.0001703786,0.0004570983],"domain_scores_gemma":[0.9989958,0.0003176653,0.000106543,0.0002238711,0.0001616568,0.000194451],"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":[0.00002697643,0.00005632216,0.00005438047,0.00003437019,0.00001028538,0.000003965251,0.00004401051,0.08371248,0.9155939,0.00002670237,0.000340321,0.00009633767],"study_design_scores_gemma":[0.0007520504,0.00001087323,0.00005650154,0.0001041712,0.00001713766,0.000002340913,0.000008449733,0.4274189,0.571186,0.000008967585,0.0002986001,0.0001359577],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5846148,0.0001697794,0.4142461,0.0001494024,0.0005718732,0.0001053988,0.0000137686,0.0001104061,0.00001848053],"genre_scores_gemma":[0.8290375,0.000002651454,0.1702493,0.0001216051,0.0001130565,0.00001780661,0.00002277942,0.00002698398,0.0004083063],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3444078,"threshold_uncertainty_score":0.8770245,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01776866946458048,"score_gpt":0.2378927510977124,"score_spread":0.2201240816331319,"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."}}