{"id":"W4385699033","doi":"10.2139/ssrn.4535818","title":"Machine Learning Estimation of Reaction Energy Barriers","year":2023,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Machine Learning in Materials Science","field":"Materials Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"","keywords":"Estimation; Energy (signal processing); Computer science; Artificial intelligence; Economics; Statistics; Mathematics; Management","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":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.007568125,0.0003464378,0.0005257506,0.0003842782,0.0003952731,0.0002099745,0.0009228632,0.0002818253,0.0002362723],"category_scores_gemma":[0.001441871,0.0003235302,0.0001842496,0.0002515315,0.0001485768,0.0002628248,0.0005007939,0.003373599,0.0001025961],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001040852,"about_ca_system_score_gemma":0.003107199,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002376062,"about_ca_topic_score_gemma":0.0004441829,"domain_scores_codex":[0.9951382,0.0007001078,0.0008259327,0.0005697411,0.00084552,0.001920536],"domain_scores_gemma":[0.9976671,0.0001384088,0.001460062,0.0004071114,0.0001765609,0.0001507609],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001271692,0.00002982478,0.0006209289,0.0001280173,0.00007161128,0.000008460269,0.0003736891,0.6438639,0.3136583,0.0337064,0.00007134357,0.007340433],"study_design_scores_gemma":[0.0007065287,0.0006799931,0.0005602652,0.0004762381,0.0001768183,0.0005475475,0.0007044328,0.3300492,0.03364512,0.6301152,0.001371188,0.0009674914],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7619793,0.001498487,0.228666,0.0009806211,0.005487978,0.0002384607,0.00003354347,0.0005432522,0.0005723588],"genre_scores_gemma":[0.9922542,0.002759988,0.001911908,0.00002598034,0.0003723157,0.000017121,0.00005283755,0.00007791677,0.002527755],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5964088,"threshold_uncertainty_score":0.9999217,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01000570808167031,"score_gpt":0.2627282895496155,"score_spread":0.2527225814679452,"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."}}