{"id":"W2960588519","doi":"","title":"An Application of the Gibbs Sampling to the Battleship Game","year":2019,"lang":"en","type":"article","venue":"MacEwan University Student Research Proceedings","topic":"Statistical Mechanics and Entropy","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"MacEwan University","funders":"","keywords":"Gibbs sampling; Mathematical economics; Computer science; Econometrics; Mathematics; Artificial intelligence; Bayesian probability","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002239144,0.0005658814,0.001285731,0.001015433,0.0009305581,0.001294075,0.001798228,0.001245624,0.006332906],"category_scores_gemma":[0.0153998,0.0005297304,0.00111751,0.00127889,0.002428796,0.002682331,0.002520587,0.001795259,0.0003176623],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001223262,"about_ca_system_score_gemma":0.00201093,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009195814,"about_ca_topic_score_gemma":0.008751628,"domain_scores_codex":[0.9988942,0.0007063593,0.00002987895,0.0001084249,0.0001555642,0.0001056347],"domain_scores_gemma":[0.9929765,0.00617569,0.0001150029,0.0002590831,0.0002116738,0.0002619652],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001117083,0.00008563817,0.001188832,0.00008056348,0.00005197557,0.0001289358,0.0002497298,0.2354025,0.0005330622,0.7297112,0.002592448,0.02986342],"study_design_scores_gemma":[0.00002034985,0.00002079752,0.0002268283,0.000009522361,0.000007695244,0.00003377345,0.00002340242,0.7574522,0.0001070137,0.2410923,0.0009953592,0.00001073795],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05310204,0.0006711324,0.923986,0.001191157,0.0001884636,0.0001016892,0.00008903868,0.0001474478,0.02052308],"genre_scores_gemma":[0.78316,0.00112642,0.1994982,0.0003640405,0.0004474411,0.000214932,0.0001791013,0.0002112375,0.01479862],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009195814,"threshold_uncertainty_score":0.0211857,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05500152334067229,"score_gpt":0.3689219682489232,"score_spread":0.3139204449082509,"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."}}