{"id":"W23995389","doi":"10.1038/nmeth.2641","title":"Определение качества социологического инструментария на основе анализа невербальных реакций респондентов (результаты эксперимента)","year":2013,"lang":"en","type":"article","venue":"Monitoring obŝestvennogo mneniâ: èkonomičeskie i socialʹnye peremeny","topic":"Genetics, Aging, and Longevity in Model Organisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of General Medical Sciences; National Cancer Institute; Canadian Institutes of Health Research; National Institutes of Health; Howard Hughes Medical Institute","keywords":"Computer science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["metaepi_narrow"],"category_scores_codex":[0.000842886,0.001348909,0.001114457,0.0002929951,0.001171503,0.0006605005,0.001706275,0.001122836,0.0005819146],"category_scores_gemma":[0.0003060259,0.001510735,0.0007508212,0.0004293149,0.0005567754,0.000107279,0.0009125712,0.0009316988,0.001236355],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004618575,"about_ca_system_score_gemma":0.0005642414,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001295684,"about_ca_topic_score_gemma":0.0001904995,"domain_scores_codex":[0.9930317,0.0003681726,0.001436118,0.00201223,0.0009254589,0.00222636],"domain_scores_gemma":[0.9957692,0.0001031022,0.0006530694,0.001963966,0.0006677094,0.0008429295],"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":[0.0001775508,0.001112814,0.1820166,0.0003068642,0.001048582,0.0000462173,0.003953491,0.0009758275,0.7459394,0.0007106174,0.03672637,0.02698569],"study_design_scores_gemma":[0.007401867,0.001966788,0.3252909,0.0003766708,0.000772221,0.0001276802,0.004640358,0.0005689589,0.4360993,0.006105513,0.2092024,0.007447352],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9811195,0.002290869,0.00156404,0.001263814,0.00512442,0.001457393,0.00007550258,0.0003650479,0.006739375],"genre_scores_gemma":[0.9790501,0.001032364,0.004808753,0.0005742689,0.008047707,0.0004929426,0.0002348058,0.0003810756,0.005377953],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3098401,"threshold_uncertainty_score":0.9999262,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01466229624282835,"score_gpt":0.238439055076402,"score_spread":0.2237767588335737,"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."}}