{"id":"W6888873858","doi":"10.24433/co.6244256.v1","title":"Renewal Monte Carlo","year":2019,"lang":"en","type":"other","venue":"Code Ocean","topic":"","field":"","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Monte Carlo method; Markov decision process; Markov chain Monte Carlo; Markov process; Reinforcement learning; Particle filter; Renewal theory; Hybrid Monte Carlo","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001059482,0.0003894666,0.0004515481,0.0002915544,0.00002033855,0.00003741764,0.0005207573,0.0004088618,0.002288452],"category_scores_gemma":[0.00003397572,0.0003819521,0.0001416016,0.000148381,0.00007064628,0.0000236235,0.0001217168,0.0002595426,0.07903448],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001199732,"about_ca_system_score_gemma":0.0001067271,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005965794,"about_ca_topic_score_gemma":0.001129757,"domain_scores_codex":[0.9985018,0.00005630197,0.0001679493,0.0005309362,0.0003481278,0.000394899],"domain_scores_gemma":[0.9984093,0.00001569722,0.0002302245,0.001190265,0.00003065097,0.0001239017],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001109552,0.00002010014,0.0004248316,0.00005569295,0.00008628437,0.00002458318,0.00005588275,0.000009637486,0.00003924501,0.0001656697,0.999006,0.0001009983],"study_design_scores_gemma":[0.0004353198,0.00002300431,0.00002918466,0.0002269059,0.00006412767,0.000006027364,0.00001483874,0.00007294548,0.00002500167,0.0000265832,0.9986383,0.0004377543],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0001974695,0.001996671,0.000002326371,0.00003044245,0.0009257349,0.0003934632,0.001549158,0.001098964,0.9938058],"genre_scores_gemma":[0.00279427,0.00003628776,0.0001725949,0.00007999361,0.0008530165,0.000002208149,0.0000898837,0.004180603,0.9917911],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.07674602,"threshold_uncertainty_score":0.9998633,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01608740810444235,"score_gpt":0.2495830898333894,"score_spread":0.2334956817289471,"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."}}