{"id":"W2254389673","doi":"10.1007/s11426-013-5022-6","title":"Cluster-in-molecule local correlation method for large systems","year":2013,"lang":"en","type":"article","venue":"Science China Chemistry","topic":"Advanced Chemical Physics Studies","field":"Physics and Astronomy","cited_by":26,"is_retracted":false,"has_abstract":false,"ca_institutions":"Ministry of Education and Child Care","funders":"","keywords":"Cluster (spacecraft); Perturbation theory (quantum mechanics); Electronic correlation; Coupled cluster; Linear scale; Correlation; Atomic orbital; Statistical physics; Computer science; Scaling; Molecule; Physics; Electron; Mathematics; Quantum mechanics","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":[0.0001787066,0.0001265536,0.0001555318,0.00001584449,0.0001697178,0.00005348904,0.000247611,0.00002713395,0.00003875839],"category_scores_gemma":[0.00002890547,0.000116169,0.00005120492,0.0002676912,0.0001405159,0.0002698948,0.000113577,0.0001307895,0.00001612693],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009430392,"about_ca_system_score_gemma":0.00005816415,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000076756,"about_ca_topic_score_gemma":2.118036e-7,"domain_scores_codex":[0.9989029,0.000006066766,0.0001742347,0.0003438865,0.0001787545,0.0003942241],"domain_scores_gemma":[0.999459,0.00006740978,0.00008580532,0.0002026444,0.0001046528,0.00008051188],"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":[0.00001076362,0.0002396997,0.003787488,0.000153789,0.0000197822,3.20147e-7,0.0006095837,0.02708319,0.9525453,0.009503051,0.001370952,0.00467611],"study_design_scores_gemma":[0.0009181567,0.00001297511,0.0003163274,0.00006412494,0.000010727,7.614804e-7,0.002237353,0.2775266,0.6267015,0.09154947,0.0002791553,0.0003827769],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2441314,0.00002829209,0.7377197,0.00008631945,0.0001080703,0.0002850842,0.00001811593,0.00002194213,0.01760115],"genre_scores_gemma":[0.9960433,2.221491e-7,0.00306048,0.00001521639,0.0001672247,0.00015633,0.00001679475,0.00001022503,0.0005302121],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7519119,"threshold_uncertainty_score":0.4737235,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004895704487122132,"score_gpt":0.2694211398682932,"score_spread":0.2645254353811711,"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."}}