{"id":"W3216017632","doi":"10.1038/s41597-021-01088-2","title":"BSE49, a diverse, high-quality benchmark dataset of separation energies of chemical bonds","year":2021,"lang":"en","type":"article","venue":"Scientific Data","topic":"Free Radicals and Antioxidants","field":"Chemistry","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia","funders":"Agencia Estatal de Investigación; British Columbia Knowledge Development Fund; Natural Sciences and Engineering Research Council of Canada; University of British Columbia; Ministerio de Ciencia e Innovación; Western Canada Research Grid; Compute Canada","keywords":"Molecule; Covalent bond; Homolysis; Chemistry; Bond energy; Sextuple bond; Bond cleavage; Computational chemistry; Bond length; Radical; Bond order; Organic chemistry","routes":{"ca_aff":true,"ca_fund":true,"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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005978604,0.00009480381,0.0002288283,0.00003086002,0.00006361272,0.00006932402,0.00090112,0.00007205327,0.002548964],"category_scores_gemma":[0.0003858704,0.00009003576,0.00003561535,0.0003075505,0.0004632806,0.0003091884,0.001064421,0.00008105298,0.0000153533],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001195942,"about_ca_system_score_gemma":0.000148927,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000113578,"about_ca_topic_score_gemma":0.0000408944,"domain_scores_codex":[0.9982879,0.0000286249,0.0004403925,0.0005787048,0.0004914934,0.0001728711],"domain_scores_gemma":[0.9973531,0.00007083412,0.0002041506,0.002187027,0.000116275,0.00006855415],"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":[0.000008816887,0.0001408021,0.0002817744,0.0001521236,0.00002026675,0.000005116418,0.00002212996,0.000003458901,0.7494241,0.000849281,0.2480977,0.0009943836],"study_design_scores_gemma":[0.0002737456,0.000003198059,0.0003230438,0.00006035483,0.00003175527,0.000002913269,0.000117471,0.000345442,0.9285222,0.000273229,0.06993828,0.0001083835],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8482012,0.0002582982,0.000038907,0.00006290934,0.000263226,0.0000191979,0.1497973,0.00001453545,0.00134447],"genre_scores_gemma":[0.838686,0.00001651446,0.001425024,0.00001214229,0.00005453043,0.000001121105,0.1586402,0.000005515176,0.00115889],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1790981,"threshold_uncertainty_score":0.9983628,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06207301716514937,"score_gpt":0.3402202235745776,"score_spread":0.2781472064094282,"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."}}