{"id":"W2032301741","doi":"10.1198/jasa.2003.s307","title":"Multivariate Dispersion, Central Regions and Depth: the Lift Zonoid Approach. Karl Mosler","year":2003,"lang":"en","type":"article","venue":"Journal of the American Statistical Association","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Lift (data mining); Multivariate statistics; Dispersion (optics); Geology; Mathematics; Geodesy; Statistics; Geography; Environmental science; Computer science; Physics; Optics; Data mining","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":[0.001256783,0.0001443277,0.0003869115,0.00003207164,0.0002458578,0.0000826188,0.0002138083,0.00004635605,0.00003039431],"category_scores_gemma":[0.01843457,0.00007417951,0.0001075293,0.0002577899,0.0002564629,0.00007718916,0.00004435462,0.0004473772,0.000002533772],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002037498,"about_ca_system_score_gemma":0.00008407597,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005167153,"about_ca_topic_score_gemma":0.000009257558,"domain_scores_codex":[0.997318,0.001197241,0.0005153038,0.0001394539,0.0005117214,0.0003182524],"domain_scores_gemma":[0.9926101,0.005678814,0.001165379,0.0001863113,0.0002096537,0.0001497276],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00005594918,0.0002121838,0.0194295,0.00001898665,0.0001715377,0.000004896243,0.0006313539,0.000006276397,0.0001823104,0.9531737,0.01151091,0.01460238],"study_design_scores_gemma":[0.0005116411,0.0001603211,0.258237,0.00003775135,0.00032137,0.00005579544,0.0006897236,0.001960213,0.00006138637,0.735979,0.0018112,0.0001746931],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0151082,0.00002938474,0.9813469,0.002073709,0.0002304145,0.0001518567,0.00005478893,0.000009002253,0.0009957619],"genre_scores_gemma":[0.4774053,0.00003932382,0.5219342,0.0003498184,0.0001111692,0.000003652229,7.844944e-7,0.00001562311,0.0001401605],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4622971,"threshold_uncertainty_score":0.9898336,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03287875679416995,"score_gpt":0.3282740394970484,"score_spread":0.2953952827028784,"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."}}