{"id":"W4408923730","doi":"10.1021/acs.nanolett.5c00343","title":"Microscopic Kinetics of Water Adsorption in Metal–Organic Frameworks","year":2025,"lang":"en","type":"article","venue":"Nano Letters","topic":"NMR spectroscopy and applications","field":"Physics and Astronomy","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Research Grants Council, University Grants Committee","keywords":"Adsorption; Kinetics; Metal-organic framework; Metal; Materials science; Chemistry; Chemical engineering; Physical chemistry; Metallurgy; Physics","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":[0.0001627026,0.0002601331,0.0001692251,0.0002336479,0.0003750989,0.0002823238,0.0005136807,0.0003446637,0.001385596],"category_scores_gemma":[0.0003341849,0.0001657177,0.0002482114,0.000161529,0.0004060444,0.0005624099,0.0001788768,0.0004774864,0.0001270469],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001132259,"about_ca_system_score_gemma":0.0002858227,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009534236,"about_ca_topic_score_gemma":0.004161952,"domain_scores_codex":[0.999886,0.000006940199,0.000003517387,0.00002798208,0.00003429113,0.00004117816],"domain_scores_gemma":[0.9999132,0.00003681394,0.00001711335,0.000007606004,0.00001553573,0.000009700305],"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":[0.0003102128,0.0001480805,0.003783232,0.0002067687,0.00005496059,0.0002677086,0.0002147854,0.05265871,0.9219956,0.01099912,0.0009556715,0.008405226],"study_design_scores_gemma":[0.00004390848,0.000206147,0.009075155,0.00001270817,0.00002550376,0.00006964854,0.0001466031,0.5189072,0.4674208,0.001989474,0.002024226,0.00007865726],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9922509,0.000334528,0.004431242,0.0001203579,0.00001857767,0.00001493527,0.0002151976,0.0001330242,0.002481202],"genre_scores_gemma":[0.9988316,0.000111815,0.0006282844,0.000008965527,0.000003506808,0.000008676329,0.00005920155,0.000005940393,0.0003420344],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009534236,"threshold_uncertainty_score":0.0189575,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003826418177990447,"score_gpt":0.2729478293168979,"score_spread":0.2691214111389074,"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."}}