{"id":"W4385500468","doi":"10.2139/ssrn.4528742","title":"Optimal Staking and Liquid Token Holding Decisions in Cryptocurrency Markets","year":2023,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Blockchain Technology Applications and Security","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Cryptocurrency; Security token; Business; Token economy; Commerce; Economics; Computer science; Computer security; Psychology; Social psychology","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":[],"consensus_categories":[],"category_scores_codex":[0.002102155,0.0001088308,0.0001331174,0.0004292554,0.0002972253,0.00008872643,0.0007195077,0.00009805048,0.000003609683],"category_scores_gemma":[0.0001125113,0.0001041323,0.00003987161,0.0009870984,0.00004370356,0.0002519022,0.0003142658,0.001452651,0.00001568511],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002093685,"about_ca_system_score_gemma":0.0004799312,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009208953,"about_ca_topic_score_gemma":0.0001000698,"domain_scores_codex":[0.9978252,0.00005790566,0.0002497203,0.0002781306,0.0001685912,0.001420442],"domain_scores_gemma":[0.9993965,0.0001388694,0.00008798399,0.0002752014,0.00003910094,0.00006234443],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00001554973,0.00003906335,0.0009455489,0.000001582756,0.0000197718,0.00001703313,0.0003628912,0.0001077751,0.0003487676,0.8066534,0.00009263475,0.191396],"study_design_scores_gemma":[0.001040518,0.0004145206,0.009408466,0.00007841284,0.000009678704,0.0009678808,0.001135888,0.06256622,0.0003567598,0.9192914,0.004302494,0.0004277315],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7806086,0.001416182,0.2155229,0.002003693,0.00007378557,0.00009176438,5.818126e-7,0.0001402847,0.0001421787],"genre_scores_gemma":[0.9897794,0.00652035,0.003560262,0.00003226932,0.00003753313,0.00001721353,6.667541e-7,0.000007668978,0.00004463217],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2119627,"threshold_uncertainty_score":0.6311126,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01330925662324786,"score_gpt":0.2641006188135661,"score_spread":0.2507913621903183,"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."}}