{"id":"W6910196821","doi":"10.48448/bn0r-mj35","title":"Sequential Core-Set Monte Carlo","year":2021,"lang":"en","type":"other","venue":"Underline Science Inc.","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Markov chain Monte Carlo; Monte Carlo method; Particle filter; Hybrid Monte Carlo; Bayesian probability; Probabilistic logic; Monte Carlo integration; Quasi-Monte Carlo method; State space; Monte Carlo molecular modeling","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":[0.0009716519,0.000567892,0.0005895947,0.001209013,0.0002727103,0.0003474558,0.001825494,0.0003500231,0.01143382],"category_scores_gemma":[0.000301305,0.0005426796,0.0001449742,0.002509212,0.002614212,0.0001811259,0.0007083366,0.0005577543,0.004980513],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005827235,"about_ca_system_score_gemma":0.002428227,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003185414,"about_ca_topic_score_gemma":0.007001868,"domain_scores_codex":[0.9949334,0.00007537226,0.000423903,0.001481311,0.002008952,0.001077078],"domain_scores_gemma":[0.9973401,0.00003845469,0.0004371438,0.001454087,0.000313501,0.0004167285],"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":[0.000009037009,0.0001106185,0.0002672646,0.00006274375,0.00007205984,0.0002544836,0.0001602857,0.0002186538,0.0137858,0.002475874,0.9807813,0.001801848],"study_design_scores_gemma":[0.0005828911,0.00006758516,0.00008029192,0.000373674,0.00008694574,0.00009264878,0.000228778,0.01193946,0.0006500412,0.0001992739,0.9847223,0.0009760985],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.00129543,0.002365563,0.0004682284,0.0001788433,0.004081694,0.0007559676,0.001435937,0.001182739,0.9882356],"genre_scores_gemma":[0.029588,0.0000796623,0.01074171,0.0004394248,0.001871893,0.00003205111,0.0004105691,0.001574834,0.9552619],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.03297374,"threshold_uncertainty_score":0.9997025,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08633940575655724,"score_gpt":0.3546824147304989,"score_spread":0.2683430089739417,"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."}}