{"id":"W6960662613","doi":"10.14473/csda/eecijk","title":"Život během pandemie (Život k nezaplacení), spojený soubor vlny 1–54","year":2024,"lang":"cs","type":"dataset","venue":"Czech Social Science Data Archive","topic":"Wheat and Barley Genetics and Pathology","field":"Agricultural and Biological Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Standards Association","funders":"","keywords":"Coronavirus disease 2019 (COVID-19)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003718441,0.0003244473,0.0005006779,0.001493604,0.002379554,0.004425202,0.0009261849,0.001286263,0.0186757],"category_scores_gemma":[0.01080324,0.0004321064,0.0008109675,0.002070248,0.001665685,0.002574988,0.004927128,0.002537956,0.00219109],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00350544,"about_ca_system_score_gemma":0.01093199,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06047399,"about_ca_topic_score_gemma":0.09281573,"domain_scores_codex":[0.9959073,0.001578019,0.0003583015,0.0005146568,0.000921607,0.0007200292],"domain_scores_gemma":[0.9956169,0.0008704806,0.001202611,0.0003097729,0.001022332,0.000977814],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007263946,0.0005849333,0.6128743,0.00370521,0.0006128587,0.00104602,0.02799202,0.0003610075,0.001917767,0.03831884,0.0528242,0.2590364],"study_design_scores_gemma":[0.00006642445,0.0005186863,0.6695482,0.00354417,0.000330884,0.001050591,0.03524068,0.0001849731,0.001326469,0.00713232,0.2809657,0.00009094727],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"dataset","genre_scores_codex":[0.6080213,0.03286272,0.006213202,0.07715894,0.002067105,0.001185277,0.01410957,0.0002128889,0.258169],"genre_scores_gemma":[0.9036299,0.02011824,0.004929334,0.007808508,0.0005075035,0.0009053675,0.003825888,0.0000830139,0.0581922],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.06047399,"threshold_uncertainty_score":0.120244,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05759155267093501,"score_gpt":0.3164924103390344,"score_spread":0.2589008576680993,"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."}}