{"id":"W2088723239","doi":"10.1002/jcc.23285","title":"Finding optimal finite field strengths allowing for a maximum of precision in the calculation of polarizabilities and hyperpolarizabilities","year":2013,"lang":"en","type":"article","venue":"Journal of Computational Chemistry","topic":"Nonlinear Optical Materials Research","field":"Materials Science","cited_by":50,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Compute Canada","keywords":"Field (mathematics); Finite field; Computational chemistry; Mathematics; Chemistry; Combinatorics; Pure mathematics","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":[],"consensus_categories":[],"category_scores_codex":[0.001052568,0.00006657451,0.0001965427,0.00004705061,0.00003265481,0.00004294372,0.0001683848,0.00006326745,0.000160161],"category_scores_gemma":[0.001856487,0.00004781694,0.00005996078,0.00006410779,0.00009603809,0.0002099909,0.00004475434,0.0001066063,4.434248e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002018772,"about_ca_system_score_gemma":0.00009083039,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002508565,"about_ca_topic_score_gemma":3.32566e-7,"domain_scores_codex":[0.9987956,0.00007634127,0.000573659,0.00008033332,0.0003651206,0.0001088909],"domain_scores_gemma":[0.9948031,0.004494958,0.0002382302,0.00006927439,0.0003644446,0.00003004715],"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":[0.0001610959,0.0000991557,0.001435827,0.0004906228,0.00001135502,9.178532e-7,0.0009919079,0.02666112,0.9692239,0.00009960471,0.00003058743,0.0007938894],"study_design_scores_gemma":[0.001049642,0.0003724379,0.01008032,0.0003727296,0.00002099694,0.00004589852,0.001956328,0.02345373,0.9285927,0.03386397,0.00005307272,0.0001381248],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.995455,0.00007443086,0.003913015,0.0002967584,0.00004629814,0.0001313956,0.00002222218,0.000001674966,0.0000592067],"genre_scores_gemma":[0.9750116,0.000003402007,0.02487244,0.00001137504,0.00007426908,0.00000458839,0.000004874559,0.00000478109,0.00001270253],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04063117,"threshold_uncertainty_score":0.2222522,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01699183131370565,"score_gpt":0.3021525227143305,"score_spread":0.2851606914006248,"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."}}