{"id":"W4398476912","doi":"10.7910/dvn/h7jroj","title":"PROSPERED Data Manual: Sick Leave","year":2019,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Data Analysis with R","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Sick leave; Computer science; Medicine; Physical therapy","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":[0.003718204,0.001171067,0.001495553,0.004287554,0.0007787447,0.00170711,0.002340332,0.001172308,0.1449],"category_scores_gemma":[0.01760236,0.0007595464,0.001211867,0.00533883,0.0003823909,0.001201252,0.001419872,0.002103797,0.1045451],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001367837,"about_ca_system_score_gemma":0.003639656,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01839629,"about_ca_topic_score_gemma":0.03407382,"domain_scores_codex":[0.9980859,0.0004049748,0.0004787591,0.0003952757,0.0004461092,0.0001891157],"domain_scores_gemma":[0.991206,0.003088059,0.001002036,0.001685864,0.002346083,0.0006720481],"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":[0.0000485584,0.00001608543,0.0007437967,0.0001634008,0.00001542254,0.00001020275,0.00001130022,0.00007835983,0.00003087793,0.0001952876,0.9958115,0.002875276],"study_design_scores_gemma":[0.0009277322,0.00007655163,0.01790071,0.0005397029,0.0000620494,0.0002506089,0.0001181766,0.0005444284,0.0003126657,0.003401406,0.9757798,0.00008624604],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001921774,0.00005836743,0.000227223,0.00007920276,0.00003027514,0.00005999888,0.9983203,0.0003901096,0.0006424157],"genre_scores_gemma":[0.0008791999,0.00007018001,0.001104074,0.000148579,0.00003570817,0.0005975692,0.9950593,0.0003301416,0.001775295],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1449,"threshold_uncertainty_score":0.4847386,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04299922808882484,"score_gpt":0.2901439242246707,"score_spread":0.2471446961358458,"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."}}