{"id":"W4398356832","doi":"10.7910/dvn/8ywcf9/lwl0sm","title":"cgss.tab","year":2019,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Digital Economy and Work Transformation","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Crowdsourcing; China; Face (sociological concept); The Internet; Data science; Business; Computer science; World Wide Web; Sociology; Political science; Social science","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001174681,0.003272023,0.002025208,0.005848136,0.001125666,0.004523963,0.004050981,0.003518353,0.2104985],"category_scores_gemma":[0.008741289,0.000954986,0.001636823,0.009993958,0.0006881866,0.002438123,0.003059538,0.002418824,0.2460203],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001837755,"about_ca_system_score_gemma":0.00281209,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01880278,"about_ca_topic_score_gemma":0.02645749,"domain_scores_codex":[0.9987962,0.0002082623,0.000148843,0.0004052213,0.000216921,0.0002244753],"domain_scores_gemma":[0.9972729,0.0008129348,0.0002632673,0.0007785875,0.0005291586,0.000343165],"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":[0.00004116757,0.00001316054,0.0003331724,0.0006751797,0.00002658212,0.00001212188,0.00001668885,0.0001381754,0.00005811563,0.0004177266,0.9971762,0.001091765],"study_design_scores_gemma":[0.0004095588,0.00002231149,0.001791346,0.0004440574,0.00003717691,0.00004590355,0.00007362158,0.0003867201,0.0002795782,0.001770238,0.9947085,0.00003088426],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004924833,0.00005433278,0.00002642839,0.00005930967,0.00002063589,0.000005911076,0.9989052,0.0003916458,0.0004872708],"genre_scores_gemma":[0.0002973882,0.00006968778,0.000120131,0.00006579948,0.00001087301,0.00005143568,0.998659,0.0001276268,0.0005980424],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7895015,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02292927640390565,"score_gpt":0.2678653922686492,"score_spread":0.2449361158647435,"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."}}