{"id":"W2887090184","doi":"10.2139/ssrn.2960470","title":"Job Tasks, Time Allocation, and Wages","year":2017,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Digital Economy and Work Transformation","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"Social Sciences and Humanities Research Council of Canada; Spencer Foundation; Andrew W. Mellon Foundation; National Science Foundation","keywords":"Time allocation; Labour economics; Computer science; Economics; Management","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001066668,0.0002432994,0.0002474737,0.0009370319,0.0008144011,0.001845215,0.0004817489,0.0006360669,0.01451428],"category_scores_gemma":[0.009869673,0.000215341,0.000293426,0.001018069,0.0005936784,0.000832624,0.001230102,0.0008147967,0.001600253],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005276881,"about_ca_system_score_gemma":0.0007539777,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005519533,"about_ca_topic_score_gemma":0.008081065,"domain_scores_codex":[0.9994112,0.0002143218,0.00003887969,0.00005127129,0.00007959842,0.0002048272],"domain_scores_gemma":[0.9910137,0.003341562,0.001969386,0.0003520626,0.00039577,0.002927506],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002416092,0.002133436,0.9528435,0.00007049949,0.000100689,0.0002412555,0.002171722,0.002142454,0.001260619,0.006052738,0.001060458,0.02950651],"study_design_scores_gemma":[0.00004799261,0.0001854613,0.9906809,0.00002215951,0.00002308965,0.0000573192,0.002760668,0.001315609,0.0001061119,0.00384755,0.000940258,0.00001294938],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9933529,0.0002432302,0.0002319605,0.0002310315,0.00001617741,0.000007527893,0.0001115338,0.00000407573,0.005801441],"genre_scores_gemma":[0.9973934,0.00008403796,0.00008725483,0.00002176865,0.00001241076,0.000008489969,0.00009149434,0.000004594432,0.00229661],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01451428,"threshold_uncertainty_score":0.04855514,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007434537512123239,"score_gpt":0.2542041451183829,"score_spread":0.2467696076062597,"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."}}