{"id":"W1557643481","doi":"10.1002/9780470987605.ch10","title":"Improving Data Behaviour for Statistical Analysis: Ranking and Transformations","year":2008,"lang":"en","type":"other","venue":"","topic":"Statistical and Computational Modeling","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Geological Survey of Canada","funders":"","keywords":"Ranking (information retrieval); Sorting; Multivariate statistics; Transformation (genetics); Data set; Set (abstract data type); Computer science; Data transformation; Data mining; Mathematics; Statistics; Information retrieval; Algorithm; Artificial intelligence; Chemistry; Data warehouse","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":[],"consensus_categories":[],"category_scores_codex":[0.0001108602,0.0001542997,0.0002638996,0.0002654583,0.0001130083,0.0001332575,0.0006190969,0.00008275593,0.00008600539],"category_scores_gemma":[0.00003747394,0.0001357156,0.00004258252,0.0002318904,0.00003679787,0.0001704256,0.0001707261,0.00008638805,0.000006535063],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009110898,"about_ca_system_score_gemma":0.00007113284,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003038965,"about_ca_topic_score_gemma":0.0001403349,"domain_scores_codex":[0.998823,0.00001983144,0.0002480951,0.0004975081,0.0002238111,0.0001877554],"domain_scores_gemma":[0.9990855,0.000280839,0.00007462315,0.0004318762,0.00004102567,0.00008606105],"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":[0.000006219288,0.00008031213,0.0001121891,0.0001525172,0.0006667656,0.00001488313,0.0001924834,0.0004367235,0.000001550529,0.6595306,0.1268128,0.211993],"study_design_scores_gemma":[0.0002194898,0.00001702434,0.0001615084,0.00001382564,0.0002965435,0.000007804858,0.000006008429,0.9898095,3.86813e-7,0.003953301,0.005315868,0.0001987866],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.000001079461,0.0002351388,0.9859109,0.000106275,0.00007709891,0.000233134,0.000926634,0.0001833074,0.01232645],"genre_scores_gemma":[0.002727385,0.00004512156,0.9848146,0.0001363528,0.00008209208,0.00002854541,0.0009454982,0.00005367186,0.01116668],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9893727,"threshold_uncertainty_score":0.553432,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04472685354965211,"score_gpt":0.2993347018271038,"score_spread":0.2546078482774517,"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."}}