{"id":"W4409837881","doi":"10.36227/techrxiv.174568376.62667034/v1","title":"The Embui Protocol: Designing a Merit-Based UBI to Complement AGI for Human Advancement","year":2025,"lang":"en","type":"preprint","venue":"","topic":"Cognitive Science and Mapping","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Complement (music); Protocol (science); Computer science; Chemistry; Medicine; Biochemistry","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":[0.001457007,0.0003108451,0.0002854598,0.000184957,0.001029328,0.0007590768,0.002465146,0.00005485542,0.00001965802],"category_scores_gemma":[0.00009804202,0.0002264165,0.000181305,0.0003622737,0.00006232045,0.0001225166,0.002623203,0.0002095411,0.00001081259],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001809089,"about_ca_system_score_gemma":0.0005877549,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008173531,"about_ca_topic_score_gemma":0.0002437537,"domain_scores_codex":[0.9972437,0.0001017497,0.0005078315,0.001015332,0.0005033962,0.0006279724],"domain_scores_gemma":[0.9978932,0.0003287802,0.0002005249,0.0009918748,0.0004520171,0.0001336172],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00009471795,0.0003790054,0.0001413836,0.001027154,0.0001487036,0.000005971631,0.001702509,0.01039642,0.005791653,0.3915456,0.02337507,0.5653918],"study_design_scores_gemma":[0.001350613,0.0005699719,0.0002014891,0.001116951,0.00002369287,3.449306e-7,0.0003076505,0.08466192,0.02830198,0.03081137,0.8517841,0.0008699385],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"protocol","genre_scores_codex":[0.00001472011,0.000006948825,0.8885705,0.006547477,0.0003565233,0.1002441,0.00001300663,0.0001704462,0.004076289],"genre_scores_gemma":[0.004650815,8.884764e-7,0.4621788,0.003919685,0.000112246,0.5260214,0.00001381072,0.00001118121,0.003091125],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.828409,"threshold_uncertainty_score":0.9232996,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08549106732926938,"score_gpt":0.4109500062143726,"score_spread":0.3254589388851032,"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."}}