{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0006535268,0.0003166521,0.0004482041,0.001247753,0.0009106745,0.001565521,0.0004198766,0.0005535165,0.008997896],"category_scores_gemma":[0.001046975,0.0005819005,0.0003318008,0.001247859,0.0008733269,0.0007593789,0.0006619049,0.0009961806,0.004204477],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006882289,"about_ca_system_score_gemma":0.001654867,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001605984,"about_ca_topic_score_gemma":0.003398292,"domain_scores_codex":[0.9992858,0.00008553915,0.00004098354,0.0001480472,0.0003567131,0.00008301546],"domain_scores_gemma":[0.9994357,0.0001330617,0.0001311436,0.0001022816,0.0001512653,0.00004643456],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002498172,0.0001160428,0.002598081,0.0006316085,0.00005172993,0.001030438,0.0006679438,0.002498099,0.586977,0.1030741,0.004487727,0.2976174],"study_design_scores_gemma":[0.00008652107,0.0003015184,0.005843054,0.0001813939,0.0001145295,0.002522606,0.0005752298,0.003426682,0.4343611,0.0248682,0.5274794,0.0002397242],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3238725,0.0565183,0.3510706,0.002982296,0.002409397,0.0004275117,0.002112262,0.001105108,0.2595021],"genre_scores_gemma":[0.7809706,0.02185842,0.1600402,0.0002572671,0.0002687769,0.000604992,0.0007323498,0.0003644224,0.03490292],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9993465,"threshold_uncertainty_score":0.03010094,"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."}}