{"id":"W4239226520","doi":"10.1360/csb2012-57-33-3208","title":"砷对核苷酸切除修复的抑制","year":2012,"lang":"ja","type":"article","venue":"Chinese Science Bulletin (Chinese Version)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science","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":["metaresearch","metaepi_narrow","sts","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":["metaepi_narrow","sts","insufficient_payload"],"category_scores_codex":[0.01016315,0.002344002,0.001669839,0.002721711,0.004400414,0.001122142,0.005989222,0.0005905881,0.0370757],"category_scores_gemma":[0.009657855,0.001745323,0.0009318832,0.01618195,0.006890405,0.003787069,0.00414478,0.001803592,0.3956648],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001629987,"about_ca_system_score_gemma":0.001090318,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003385471,"about_ca_topic_score_gemma":0.00001359086,"domain_scores_codex":[0.9833521,0.0006553798,0.001655727,0.002874507,0.00577106,0.005691196],"domain_scores_gemma":[0.9885494,0.0008669672,0.001030079,0.003858475,0.001364305,0.004330798],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005978877,0.002393899,0.7674888,0.0002307994,0.00008619425,0.00008516348,0.005646005,0.0001323251,0.04133275,0.000437844,0.1806209,0.0009474016],"study_design_scores_gemma":[0.004314004,0.0002918257,0.5972726,0.0002620702,0.0002019862,0.0004777849,0.001007107,0.003048572,0.0005751174,0.0002680134,0.3892024,0.00307847],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9071743,0.003637048,0.00003303926,0.004903049,0.01326453,0.001160394,0.0003670651,0.0008293577,0.06863122],"genre_scores_gemma":[0.9796898,0.0001236184,0.00271876,0.001445791,0.004076618,0.00005000641,0.00009732649,0.0004196199,0.01137844],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3585891,"threshold_uncertainty_score":0.9999148,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008737483025343292,"score_gpt":0.2677151990767579,"score_spread":0.2589777160514147,"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."}}