{"id":"W4205642101","doi":"10.1039/d1ta09221a","title":"Demystifying constructive strategies on designing functionalized lamellar Nb<sub>2</sub>CT<sub><i>x</i></sub> nanosheet membrane architectures under confined space","year":2022,"lang":"en","type":"article","venue":"Journal of Materials Chemistry A","topic":"Membrane Separation Technologies","field":"Environmental Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Nanosheet; Lamellar structure; Membrane; Ion; Constructive; Materials science; Space (punctuation); Permeation; Nanotechnology; Chemical engineering; Chemistry; Computer science; Composite material; Engineering; Organic 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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008962757,0.0003671466,0.0005698996,0.00008930381,0.0004379785,0.0001751039,0.0004987046,0.0001159238,0.003496016],"category_scores_gemma":[0.0002427196,0.0003439857,0.0001453078,0.0002587594,0.0004170155,0.0001955989,0.0002784789,0.0005305643,0.00003736634],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003413191,"about_ca_system_score_gemma":0.0001578652,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008910171,"about_ca_topic_score_gemma":0.000002302034,"domain_scores_codex":[0.9971768,0.0002870632,0.0007881782,0.0004080597,0.0009324175,0.000407492],"domain_scores_gemma":[0.9981692,0.0002986446,0.001056321,0.0003033654,0.000046303,0.0001261631],"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":[0.0006687843,0.00006969827,0.00002323784,0.00007203636,0.00009550305,0.0001144113,0.000120394,0.06926494,0.928621,0.00009340498,0.0005934594,0.0002631408],"study_design_scores_gemma":[0.001267247,0.0001510072,0.0001382854,0.00006474704,0.00006370476,0.001259301,0.001729543,0.00002238591,0.9915408,0.002893789,0.0005259654,0.0003431512],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9961951,0.00007288629,0.0005908044,0.0006384552,0.0004187164,0.0002208918,0.00006285151,0.00009074551,0.001709504],"genre_scores_gemma":[0.9987919,0.00005639057,0.0006882249,0.0001947795,0.0001389609,0.00003310509,0.00001931777,0.00003416498,0.00004319511],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06924256,"threshold_uncertainty_score":0.9999012,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01313300865775154,"score_gpt":0.2244248713252797,"score_spread":0.2112918626675282,"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."}}