{"id":"W6892242059","doi":"10.48660/19090120","title":"Markov Chain Monte Carlo","year":2019,"lang":"it","type":"other","venue":"PIRSA","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Perimeter Institute","funders":"","keywords":"Markov chain Monte Carlo; Monte Carlo method; Markov chain; Markov process; Particle filter; 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":[0.0006867519,0.001208165,0.001381564,0.0007151308,0.00008165801,0.0001587522,0.001155484,0.001161827,0.04242638],"category_scores_gemma":[0.0001486774,0.001253789,0.0005314266,0.0005172016,0.0002047474,0.00009651516,0.0004076238,0.0009855246,0.6666451],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007018374,"about_ca_system_score_gemma":0.0003396976,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002037453,"about_ca_topic_score_gemma":0.0006862095,"domain_scores_codex":[0.9952392,0.0003882941,0.0005997824,0.001425706,0.001012809,0.001334194],"domain_scores_gemma":[0.9961088,0.0001233435,0.0007771199,0.002513509,0.0001203782,0.0003568985],"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":[0.0001145151,0.0001909388,0.001772069,0.0004605754,0.0006684921,0.0001287647,0.0007150015,0.00003550356,0.0004849632,0.000314683,0.990186,0.004928508],"study_design_scores_gemma":[0.001376022,0.0001071502,0.001391902,0.0009033972,0.0003268984,0.00001816056,0.000113376,0.0007800709,0.00002815017,0.00001149188,0.9935982,0.001345205],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.000893482,0.007273819,0.0000113849,0.0002569409,0.003065007,0.001824517,0.001820165,0.0004555185,0.9843991],"genre_scores_gemma":[0.0140751,0.0002974079,0.0003023979,0.0002788386,0.002324058,0.00007066465,0.00007620313,0.004236427,0.9783389],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.6242187,"threshold_uncertainty_score":0.9989912,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01291761140176136,"score_gpt":0.2383364204579529,"score_spread":0.2254188090561916,"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."}}