{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001334355,0.0005625632,0.001152653,0.001149406,0.0004458041,0.001251202,0.001547253,0.001522482,0.002878989],"category_scores_gemma":[0.007663053,0.0006253586,0.0007701104,0.0006743319,0.0005589714,0.001660549,0.0008171728,0.001894648,0.0007664479],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009070064,"about_ca_system_score_gemma":0.0008666241,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002308422,"about_ca_topic_score_gemma":0.001860619,"domain_scores_codex":[0.9996742,0.0001234987,0.00001358296,0.0001022545,0.00004914328,0.00003731742],"domain_scores_gemma":[0.9956626,0.003516415,0.0002927062,0.0002211174,0.000214871,0.00009229719],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002538651,0.0001695219,0.001453948,0.0001877002,0.00005656425,0.00004307608,0.00003707951,0.9178714,0.00387226,0.02599602,0.001409189,0.04864937],"study_design_scores_gemma":[0.000005416349,0.000004515889,0.00009206165,0.000003136932,0.000001838898,0.000002702533,0.000001626516,0.9933718,0.0004160181,0.006041739,0.00005678909,0.000002272109],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1864063,0.001187987,0.803297,0.0009499953,0.0001311777,0.00008326877,0.000466215,0.001675623,0.00580238],"genre_scores_gemma":[0.8990235,0.0003436436,0.09596504,0.0001184454,0.00008039633,0.0001438056,0.0006204728,0.0001900504,0.003514743],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002878989,"threshold_uncertainty_score":0.009631217,"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."}}