{"id":"W4400273375","doi":"10.1021/acs.jctc.4c00418","title":"Machine Learning Classification of Local Environments in Molecular Crystals","year":2024,"lang":"en","type":"article","venue":"Journal of Chemical Theory and Computation","topic":"Machine Learning in Materials Science","field":"Materials Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Division of Chemistry; Natural Sciences and Engineering Research Council of Canada; Division of Materials Research; Deutsche Forschungsgemeinschaft; National Science Foundation","keywords":"Computer science; Artificial intelligence; Data science; Machine learning; Human–computer interaction","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":[0.00188952,0.00006211516,0.0001435468,0.00008256399,0.00001473571,0.00004209028,0.00009302264,0.00003884039,0.00006593736],"category_scores_gemma":[0.0001392258,0.00005024023,0.00002946854,0.00009304948,0.0001281389,0.0001607228,0.00003167192,0.0001526645,0.000004420452],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003012582,"about_ca_system_score_gemma":0.00001802362,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001481243,"about_ca_topic_score_gemma":2.948984e-8,"domain_scores_codex":[0.9989197,0.0003132079,0.0003642279,0.0001100408,0.0002142981,0.00007847097],"domain_scores_gemma":[0.9994622,0.0002609237,0.0001875487,0.00003625049,0.00001833107,0.00003469886],"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":[0.00007926228,0.00002197001,0.00009226875,0.00004645646,0.000002839189,0.00001100819,0.0002182034,0.02046614,0.9675038,0.006340656,0.000001593688,0.005215826],"study_design_scores_gemma":[0.0002426775,0.0001112,0.0007553098,0.0001837389,0.00001497952,0.00007662133,0.0001129824,0.1110654,0.8389956,0.04824587,0.0001147366,0.00008089362],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7022615,0.0003703488,0.2971402,0.00005583156,0.0000784405,0.00002280441,7.234653e-7,0.000005368555,0.0000647579],"genre_scores_gemma":[0.9973674,0.0000154241,0.002559684,0.00001543794,0.00002419655,6.511393e-7,0.000001702022,0.000005540073,0.000009956927],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2951059,"threshold_uncertainty_score":0.2048737,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00840203130409472,"score_gpt":0.2651532622289681,"score_spread":0.2567512309248733,"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."}}