{"id":"W4318460119","doi":"10.54097/hset.v26i.3639","title":"Environmental Consequences of Mining Bitcoin: The Carbon Emission in China","year":2022,"lang":"en","type":"article","venue":"Highlights in Science Engineering and Technology","topic":"Blockchain Technology Applications and Security","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Greenhouse gas; Cryptocurrency; Government (linguistics); China; Focus (optics); Electricity; Natural resource economics; Carbon credit; Environmental economics; Business; Computer science; Computer security; Engineering; Economics; Law; Political science; Geology","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":[0.0003790137,0.0003566164,0.0002545029,0.001595181,0.001108133,0.0008570567,0.0003863684,0.0006745202,0.001212712],"category_scores_gemma":[0.0004442247,0.0001456537,0.0004600057,0.002745215,0.0006724191,0.0009118828,0.0007674434,0.000417346,0.00008030795],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003613106,"about_ca_system_score_gemma":0.002557273,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1262491,"about_ca_topic_score_gemma":0.1376682,"domain_scores_codex":[0.9996544,0.00003533557,0.00002337098,0.00004381809,0.0001309559,0.0001120724],"domain_scores_gemma":[0.9995222,0.00004764791,0.0001661121,0.00002608717,0.0001484343,0.00008947123],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000267484,0.0002036728,0.9266667,0.0002577446,0.0001399541,0.006988802,0.001909771,0.01491835,0.004651399,0.005602269,0.00396063,0.03443324],"study_design_scores_gemma":[0.00001316154,0.00008328062,0.9746582,0.00003348043,0.00005294234,0.0004455181,0.002566307,0.01400932,0.001631475,0.001892438,0.004564279,0.00004966012],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9959652,0.0003351478,0.0001236717,0.0007215159,0.000007836366,0.000009476734,0.0002836034,0.000008062351,0.002545437],"genre_scores_gemma":[0.9980211,0.0005235318,0.00004645612,0.00006444476,0.000007428975,0.0000045042,0.000218773,0.000002368482,0.001111405],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1262491,"threshold_uncertainty_score":0.2510285,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003952046862526059,"score_gpt":0.1892891602140091,"score_spread":0.1853371133514831,"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."}}