{"id":"W4240719180","doi":"10.1080/15216540701629282","title":"Unholy errors","year":2007,"lang":"pt","type":"article","venue":"IUBMB Life","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"SaskTel (Canada)","funders":"","keywords":"Citation; Computer science; Library 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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001605361,0.0003904374,0.0003482242,0.0001765842,0.0001946231,0.00009359006,0.0007179576,0.000782599,0.0003040528],"category_scores_gemma":[0.001239575,0.0003607156,0.0002697808,0.000308945,0.0005265597,0.000007076751,0.0004863929,0.0004342819,0.0008797499],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005085415,"about_ca_system_score_gemma":0.0005897009,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004887145,"about_ca_topic_score_gemma":0.0001363211,"domain_scores_codex":[0.9963972,0.00007607355,0.0008476292,0.0005403922,0.0008411414,0.001297543],"domain_scores_gemma":[0.9973993,0.00006238691,0.0001953173,0.0007929942,0.0002906652,0.001259383],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00153431,0.00148126,0.01857949,0.00127032,0.001154427,0.0002052468,0.002185106,0.00003216634,0.2150539,0.0005010891,0.5485917,0.209411],"study_design_scores_gemma":[0.001758407,0.00134237,0.0150555,0.0000787391,0.00007125078,0.00003042474,0.001973378,0.000356174,0.09040979,0.00007328815,0.8879976,0.0008530755],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8974634,0.01037159,0.02060213,0.005533437,0.004486261,0.001162361,0.0002871414,0.00008207814,0.06001156],"genre_scores_gemma":[0.974369,0.001547056,0.0008298588,0.003020185,0.001785222,0.000006994224,0.0002440192,0.00005275317,0.01814486],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3394059,"threshold_uncertainty_score":0.9998982,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02505243581865806,"score_gpt":0.3143478413781585,"score_spread":0.2892954055595004,"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."}}