{"id":"W4386396592","doi":"10.1111/eufm.12451","title":"Is bitcoin ESG‐compliant? A sober look","year":2023,"lang":"en","type":"article","venue":"European Financial Management","topic":"Blockchain Technology Applications and Security","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Transparency (behavior); Corporate governance; Criticism; Element (criminal law); Compensation (psychology); Business; Accounting; Focus (optics); Environmental economics; Economics; Computer security; Political science; Psychology; Finance; Law; Social psychology; Computer 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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003635135,0.0001400333,0.0001156772,0.0002430042,0.0002383522,0.00007948682,0.001303531,0.00003448394,0.00002133324],"category_scores_gemma":[0.0000109732,0.0001430559,0.00006923162,0.001226672,0.00005798238,0.00008995663,0.001341904,0.0001431165,0.006461489],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002163725,"about_ca_system_score_gemma":0.00001033468,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004603008,"about_ca_topic_score_gemma":0.000002338134,"domain_scores_codex":[0.9987025,0.00005250286,0.0002121616,0.0005135394,0.0001704065,0.0003489243],"domain_scores_gemma":[0.9988719,0.0000130894,0.00005996656,0.0009764274,0.0000271688,0.00005148708],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000001296992,0.00005386599,0.0001605421,0.00001764863,0.000010542,0.0004325914,0.0002581538,0.000009328109,0.00001050503,0.6524253,0.1362783,0.2103419],"study_design_scores_gemma":[0.0003247881,0.00003884056,0.05419449,0.00002331262,0.0000074934,0.00001005601,0.00002710186,0.004065645,0.0001273048,0.03488122,0.9060191,0.0002806505],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02663426,0.0001206612,0.7035311,0.01246466,0.0006769631,0.0007993453,0.000007141432,0.00348073,0.2522852],"genre_scores_gemma":[0.9672408,0.0001518003,0.01543152,0.004348412,0.0001547893,0.00008665919,0.000006750166,0.00003635526,0.0125429],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9406065,"threshold_uncertainty_score":0.9943121,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01714119515652152,"score_gpt":0.2308568639561863,"score_spread":0.2137156687996648,"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."}}