{"id":"W4244022466","doi":"10.26434/chemrxiv.12506117","title":"A Kinetic Description of How Interfaces Accelerate Reactions in Micro-Compartments","year":2020,"lang":"en","type":"preprint","venue":"ChemRxiv","topic":"Molecular Junctions and Nanostructures","field":"Engineering","cited_by":10,"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; Chemistry; Computer science; Chemical physics; Materials science; Statistical physics; Physics; Classical mechanics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005278992,0.0009469457,0.0008220259,0.0006890232,0.000665149,0.001202934,0.001711003,0.001675245,0.006309179],"category_scores_gemma":[0.001025893,0.0005561027,0.001093008,0.0003621629,0.0007303739,0.002654617,0.0008849832,0.001521629,0.001902921],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001389255,"about_ca_system_score_gemma":0.0009158336,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001299437,"about_ca_topic_score_gemma":0.00098265,"domain_scores_codex":[0.9997974,0.00001559687,0.00001290137,0.00004706467,0.00007830214,0.00004874156],"domain_scores_gemma":[0.9997457,0.00009692601,0.00003883507,0.00003407108,0.00005769486,0.00002679981],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000514174,0.00009357274,0.0004737464,0.0003323458,0.00003112924,0.0004772239,0.0001254482,0.2182896,0.09312247,0.6737621,0.00258609,0.01065481],"study_design_scores_gemma":[0.00002352555,0.00004576236,0.0002356382,0.00002745583,0.00002141062,0.0002994048,0.00003589672,0.8347855,0.02746235,0.1301476,0.00687132,0.00004417431],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03444158,0.001609731,0.9384913,0.001071064,0.0005452106,0.0001994041,0.0004528899,0.0006023084,0.02258646],"genre_scores_gemma":[0.7750325,0.004279605,0.1577401,0.0008952501,0.0002772064,0.001053254,0.0005590641,0.0006852953,0.05947774],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006309179,"threshold_uncertainty_score":0.0211063,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03466536385176507,"score_gpt":0.2324566456475169,"score_spread":0.1977912817957518,"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."}}