{"id":"W4402674324","doi":"10.1109/csf61375.2024.00040","title":"On Separation Logic, Computational Independence, and Pseudorandomness","year":2024,"lang":"en","type":"article","venue":"","topic":"Cryptography and Data Security","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"Agence Nationale de la Recherche","keywords":"Pseudorandomness; Independence (probability theory); Computer science; Separation (statistics); Algorithm; Mathematics; Machine learning; Pseudorandom number generator; Statistics","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":[0.0001743029,0.00006234582,0.00005672702,0.0001054822,0.00006956002,0.0003579398,0.0001520262,0.00003648222,0.00004026947],"category_scores_gemma":[0.000008457044,0.00004794248,0.00002382135,0.0002777621,0.00002766155,0.0005167074,0.00006784785,0.00008679177,0.00006101821],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005225816,"about_ca_system_score_gemma":0.00002546343,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000871038,"about_ca_topic_score_gemma":0.000007090793,"domain_scores_codex":[0.9993644,0.00002391999,0.00008320978,0.0002537952,0.0001946377,0.00008003945],"domain_scores_gemma":[0.9996232,0.0001807825,0.000009593808,0.0001216962,0.00002577355,0.00003900125],"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":[0.000005488135,0.00001535679,0.00003331381,0.000008157167,0.000004951655,0.000009410348,0.0001211622,0.0002370875,0.00001273403,0.9907678,0.002317563,0.00646696],"study_design_scores_gemma":[0.0001877781,0.00004666062,0.00104273,0.00001159359,0.000001794613,0.00002216223,0.000006023251,0.2365784,0.00005988184,0.7607124,0.001252154,0.00007843318],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01565698,0.0001716354,0.9766626,0.0006480924,0.0002281671,0.00007080821,0.000006058325,0.0002098156,0.006345839],"genre_scores_gemma":[0.9800416,0.00001113357,0.01939965,0.0004835155,0.00002410075,0.000004979442,0.00001222479,0.000001735033,0.0000210763],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9643846,"threshold_uncertainty_score":0.3451622,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01284602987703796,"score_gpt":0.2893427765301259,"score_spread":0.2764967466530879,"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."}}