{"id":"W3043854701","doi":"10.1039/d0sc03189e","title":"A kinetic description of how interfaces accelerate reactions in micro-compartments","year":2020,"lang":"en","type":"article","venue":"Chemical Science","topic":"Mass Spectrometry Techniques and Applications","field":"Chemistry","cited_by":142,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Lawrence Berkeley National Laboratory; Basic Energy Sciences; Natural Sciences and Engineering Research Council of Canada; U.S. Department of Energy","keywords":"Kinetic energy; Computer science; Chemistry; Compartment (ship); Nanotechnology; Chemical physics; Materials science; Physics; Geology; Classical mechanics; Oceanography","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005344962,0.00006341097,0.00009573566,0.00003422482,0.00002948508,0.0000395272,0.0003394931,0.00003168704,0.0004491075],"category_scores_gemma":[0.00007228008,0.00005925273,0.00002115664,0.0006754344,0.0002040212,0.0001232305,0.00008757159,0.0001159586,0.000005658948],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007306507,"about_ca_system_score_gemma":0.00002256293,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001964163,"about_ca_topic_score_gemma":8.094578e-7,"domain_scores_codex":[0.999324,0.00000224528,0.0001406246,0.0002373508,0.0001409156,0.000154885],"domain_scores_gemma":[0.9996629,0.00001389602,0.00006576561,0.0001385169,0.00003405263,0.00008482151],"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":[0.000003871437,0.00004362823,0.00156314,0.00002318206,8.044323e-7,2.376833e-7,0.0000538756,0.000001100205,0.9973903,0.0005019534,0.0001628939,0.0002550402],"study_design_scores_gemma":[0.00008355558,0.000007563929,0.0004163184,0.00002160969,0.000002205612,0.000001275701,0.00004892988,0.0006787441,0.9963231,0.0005295177,0.001827531,0.00005963865],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9853585,0.00001740148,0.0001764543,0.001439029,0.000006929951,0.00004832659,0.000005073698,0.00004840333,0.01289982],"genre_scores_gemma":[0.996769,0.00001083626,0.00306005,0.00004733507,0.00001795845,0.00002283692,0.000003450092,0.000002949855,0.00006564827],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01283417,"threshold_uncertainty_score":0.4917412,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04896477012736727,"score_gpt":0.2824348637274551,"score_spread":0.2334700936000879,"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."}}