{"id":"W2008519152","doi":"10.1002/wics.128","title":"Geometry in statistics","year":2010,"lang":"en","type":"review","venue":"Wiley Interdisciplinary Reviews Computational Statistics","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Information geometry; Statistical inference; Nonparametric statistics; Euclidean geometry; Geometry; Computer science; Focus (optics); Inference; Mathematics; Statistics; Artificial intelligence","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"],"consensus_categories":[],"category_scores_codex":[0.001702212,0.001048136,0.003513369,0.0008325364,0.000238093,0.0003463551,0.002413422,0.0005527977,0.0001241924],"category_scores_gemma":[0.0003193197,0.0008814461,0.0004877987,0.001386232,0.0001848124,0.0003439883,0.002171945,0.002027133,0.0006491124],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002845726,"about_ca_system_score_gemma":0.0006687861,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005305161,"about_ca_topic_score_gemma":0.00003216048,"domain_scores_codex":[0.9933937,0.001088595,0.002804088,0.00134082,0.0006462937,0.0007265506],"domain_scores_gemma":[0.9948617,0.002045018,0.001340371,0.001196221,0.0002266813,0.0003299971],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000001461536,0.0001108295,9.509895e-7,0.005446726,0.00003076635,0.0001454865,0.0001061431,0.00001971387,1.761882e-8,0.1528048,0.02106659,0.8202665],"study_design_scores_gemma":[0.0001519656,0.00008694756,0.00000572016,0.009427024,0.0001380433,0.0002286326,0.000001602175,0.01378528,1.499398e-8,0.1748665,0.8005325,0.0007758615],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[1.289498e-8,0.493122,0.5039703,0.00002710827,0.0008271073,0.0007942276,0.0009824552,0.00004811096,0.0002286703],"genre_scores_gemma":[5.122457e-8,0.5043157,0.4942226,0.00007574501,0.0001515605,0.0001492965,0.0008035981,0.00004832944,0.0002330667],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8194907,"threshold_uncertainty_score":0.9993636,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06107983404593441,"score_gpt":0.403007021376157,"score_spread":0.3419271873302225,"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."}}