{"id":"W6961380015","doi":"10.14473/csda/vroqoi","title":"Život během pandemie (Život k nezaplacení), spojený soubor vlny 1–45","year":2023,"lang":"cs","type":"dataset","venue":"Czech Social Science Data Archive","topic":"Scientific Computing and Data Management","field":"Decision Sciences","cited_by":0,"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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow","sts","scholarly_communication","open_science","research_integrity","insufficient_payload"],"consensus_categories":["metaresearch","metaepi_narrow","sts","open_science","insufficient_payload"],"category_scores_codex":[0.04115833,0.001630712,0.00206518,0.003193813,0.009367382,0.01201654,0.05158968,0.0006417313,0.001116],"category_scores_gemma":[0.02349771,0.001442657,0.0005756994,0.01567065,0.01016021,0.004572038,0.05205577,0.002639269,0.05618586],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008590664,"about_ca_system_score_gemma":0.003427548,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004495675,"about_ca_topic_score_gemma":0.002637433,"domain_scores_codex":[0.9671854,0.001378184,0.003198099,0.01060716,0.01327445,0.004356676],"domain_scores_gemma":[0.9745555,0.00575012,0.002361769,0.01470607,0.0008516154,0.001774932],"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":[0.00008318443,0.0003130164,0.00008258851,0.00008123745,0.00008318233,0.0002066823,0.001459084,0.00002473665,0.0001549687,0.001582708,0.9358249,0.06010371],"study_design_scores_gemma":[0.0008099572,0.0001638212,0.002175581,0.0002780498,0.0002728732,0.00002021373,0.007985404,0.01072609,0.00002280358,0.006654434,0.9691647,0.001726043],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0009857276,0.0001509622,0.003798179,0.001930193,0.01797629,0.001674267,0.9700909,0.0004756972,0.002917738],"genre_scores_gemma":[0.001478373,0.0007392306,0.002419393,0.001191375,0.004178952,0.00007018817,0.9835216,0.0001166486,0.006284284],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.05837767,"threshold_uncertainty_score":0.9997971,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2709834127029522,"score_gpt":0.4613774402786523,"score_spread":0.1903940275757001,"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."}}