{"id":"W4366503129","doi":"10.1093/oso/9780192867735.001.0001","title":"Essential Statistics for Data Science","year":2023,"lang":"en","type":"book","venue":"","topic":"Statistics Education and Methodologies","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Frequentist inference; Bayesian statistics; Statistics; Statistical inference; Probability and statistics; Inference; Computer science; Bayesian inference; Bayesian probability; Mathematics; 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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.001867627,0.0001777486,0.00030569,0.0001969083,0.0001592865,0.0001078169,0.001201374,0.0001185309,0.0004089801],"category_scores_gemma":[0.02291149,0.0001580219,0.00002721327,0.0001043096,0.0004183084,0.00007309394,0.0005194979,0.0001374503,0.0002250135],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009623703,"about_ca_system_score_gemma":0.002897958,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003874591,"about_ca_topic_score_gemma":0.00003027902,"domain_scores_codex":[0.9984439,0.0000251238,0.0003340855,0.0005244694,0.0003926237,0.0002798081],"domain_scores_gemma":[0.9896529,0.008450932,0.0002126124,0.001226363,0.0003768633,0.00008032875],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000001854295,0.000006828017,9.423024e-8,0.0001484077,0.0000111544,6.792133e-7,0.00002690844,3.619519e-8,0.000003647145,0.4844948,0.5135788,0.001726754],"study_design_scores_gemma":[0.00007930677,0.00001368553,0.000001275339,0.00002713453,0.00008961573,0.000001378753,0.00004637356,0.0005652104,0.00003543774,0.7159653,0.2830257,0.0001495077],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[1.475579e-7,0.00001170471,0.8157148,0.00008287976,0.003838212,0.0004238992,0.009408418,0.0002037209,0.1703162],"genre_scores_gemma":[7.288914e-8,0.0000357681,0.4810638,0.00003365402,0.0002308028,0.00001597339,0.001315317,0.00003477321,0.5172699],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.3469536,"threshold_uncertainty_score":0.985319,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6197337350846748,"score_gpt":0.562271866590847,"score_spread":0.05746186849382773,"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."}}