{"id":"W2087593077","doi":"10.1063/1.1383068","title":"Reaction induced by a scanning tunneling microscope: Theory and application","year":2001,"lang":"en","type":"article","venue":"The Journal of Chemical Physics","topic":"Molecular Junctions and Nanostructures","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"Steacie Institute for Molecular Sciences","funders":"","keywords":"Scanning tunneling microscope; Desorption; Silicon; Observable; Quantum tunnelling; Excited state; Yield (engineering); Microscope; Atomic physics; Transition state theory; Chemistry; Foley; Resonance (particle physics); Materials science; Analytical Chemistry (journal); Condensed matter physics; Physics; Nanotechnology; Reaction rate constant; Optics; Physical chemistry; Quantum mechanics; Adsorption; Optoelectronics; Thermodynamics; Kinetics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000163761,0.00005843101,0.00007547027,0.00001219817,0.0000321461,0.00001147864,0.00006243669,0.00003375793,0.000001529119],"category_scores_gemma":[0.000013733,0.00004122012,0.00002501791,0.00008608744,0.00002034928,0.00006739986,0.000009145825,0.0002004312,8.26245e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002158909,"about_ca_system_score_gemma":0.000004493171,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002513156,"about_ca_topic_score_gemma":5.057424e-8,"domain_scores_codex":[0.9996844,0.00001868337,0.0001218967,0.00003237326,0.00007448694,0.00006815345],"domain_scores_gemma":[0.9997669,0.00004601,0.00005658444,0.00006935836,0.00003140976,0.00002970973],"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":[0.00002806897,0.000005198969,0.00000718869,0.000004560938,0.00001725602,1.97651e-7,0.00008465691,0.000201881,0.9823943,0.00007541534,0.0003279994,0.01685327],"study_design_scores_gemma":[0.000173599,0.00001287876,0.00005701763,0.00001933121,0.00004153701,0.0000658845,0.0000486531,0.001161096,0.9894381,0.00800055,0.0009188129,0.00006251643],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9466496,0.0005336649,0.05254249,0.00003266603,0.00005686098,0.00003004798,5.225995e-7,0.00001318058,0.0001409914],"genre_scores_gemma":[0.9995025,0.000128264,0.000138257,0.00004016617,0.0001743545,6.462693e-7,0.00000126672,0.00001123654,0.000003264494],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05285297,"threshold_uncertainty_score":0.1680908,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004845158804413399,"score_gpt":0.2152594395214862,"score_spread":0.2104142807170727,"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."}}