{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001555276,0.0003958779,0.0002419526,0.0002479668,0.0001793885,0.0002867674,0.0002247755,0.0003535229,0.0007937636],"category_scores_gemma":[0.0001385117,0.0001918832,0.0003379947,0.0001936189,0.0001543674,0.000444564,0.0002870316,0.000594442,0.0002927799],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002528568,"about_ca_system_score_gemma":0.0002536662,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006503924,"about_ca_topic_score_gemma":0.002370713,"domain_scores_codex":[0.9999269,0.000004281444,0.000005762005,0.00001664772,0.00002515678,0.00002131553],"domain_scores_gemma":[0.999922,0.00001236753,0.00002082684,0.000009177858,0.00001402468,0.00002145085],"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":[0.00001994578,0.00001244335,0.00004621391,0.00003376059,0.00000420208,0.00004727304,0.00001154823,0.0001646648,0.9972426,0.0001092858,0.00005658193,0.002251509],"study_design_scores_gemma":[0.000005208317,0.00005084317,0.0006249766,0.000004608402,0.000007844376,0.00006549226,0.000008957824,0.001760539,0.9963492,0.00004340813,0.001070519,0.000008438612],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.973251,0.001697997,0.01998427,0.0001164934,0.0001504742,0.00006276395,0.0003510628,0.0002121603,0.00417375],"genre_scores_gemma":[0.9840581,0.0007705657,0.0122737,0.0000510598,0.00002728313,0.00003568623,0.0002659116,0.00005280293,0.002464887],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007937636,"threshold_uncertainty_score":0.002655387,"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."}}