{"id":"W7132932934","doi":"","title":"Bada Bing, Bada Boom: Microsoft Bing’s Chinese Political Censorship of Autosuggestions in North America","year":2022,"lang":"en","type":"report","venue":"TSpace","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Censorship; Politics; Government (linguistics); China","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007125234,0.000204752,0.0001337428,0.002013389,0.002956143,0.002103014,0.0003784585,0.0005543312,0.0120335],"category_scores_gemma":[0.002038677,0.0001379248,0.0001127844,0.003451793,0.001042896,0.001275318,0.001009254,0.001086655,0.001119091],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005263111,"about_ca_system_score_gemma":0.005443383,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.6872792,"about_ca_topic_score_gemma":0.8398214,"domain_scores_codex":[0.9997005,0.00002925911,0.000009977454,0.00003715689,0.0001238467,0.00009925868],"domain_scores_gemma":[0.9982979,0.0004101441,0.0002262643,0.0001071378,0.0005728427,0.0003857019],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0001021165,0.00004269582,0.1376068,0.0001775843,0.00002670842,0.0007747123,0.02527252,0.0003104927,0.000862868,0.02820251,0.7432797,0.06334127],"study_design_scores_gemma":[0.00001429607,0.00002555141,0.550747,0.0002328713,0.00003629791,0.0002387511,0.02956037,0.0008042095,0.001664378,0.002962987,0.4136566,0.00005675255],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.56129,0.006623461,0.0005753191,0.06761725,0.0007878789,0.00009628162,0.02534992,0.0002699307,0.33739],"genre_scores_gemma":[0.7844047,0.004963548,0.0003337742,0.005139352,0.0003145662,0.00008410394,0.007943923,0.000147787,0.1966682],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6872792,"threshold_uncertainty_score":0.629125,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03997606408740702,"score_gpt":0.3697707681489629,"score_spread":0.3297947040615559,"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."}}