{"id":"W186756153","doi":"10.55016/ojs/ajer.v49i3.54982","title":"Total Information in Multivariate Data from Dual Scaling Perspectives","year":2003,"lang":"en","type":"article","venue":"Alberta Journal of Educational Research","topic":"Bayesian Modeling and Causal Inference","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Multivariate statistics; Dual (grammatical number); Scaling; Multidimensional scaling; Covariance; Variance (accounting); Perspective (graphical); Eigenvalues and eigenvectors; Covariance matrix; Statistics; Mathematics; Data Matrix; Multivariate analysis; Econometrics; Computer science; Artificial intelligence; Physics; Philosophy","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.00157454,0.00007125409,0.0001135416,0.0003487954,0.0001071156,0.0002570306,0.0008954598,0.00004802446,0.0006348016],"category_scores_gemma":[0.009863299,0.00006311101,0.00002725871,0.0004705715,0.00005492471,0.002603697,0.0001786066,0.0004702058,0.0001745159],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001226493,"about_ca_system_score_gemma":0.001374597,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001809963,"about_ca_topic_score_gemma":0.0001520374,"domain_scores_codex":[0.9982906,0.0003097848,0.0003949257,0.0001747119,0.000589513,0.0002404741],"domain_scores_gemma":[0.9932272,0.005485541,0.0001277995,0.0004050261,0.0006264485,0.0001279605],"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":[0.000102406,0.001139228,0.01411505,0.00002323469,0.0001256536,0.000004852067,0.03387739,0.004469596,0.001374696,0.9260788,0.009600796,0.009088336],"study_design_scores_gemma":[0.004292587,0.0005627108,0.2322019,0.0008922191,0.00003261678,0.0006859028,0.01635572,0.5574671,0.001511839,0.1721763,0.01268421,0.001136934],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9138097,0.0009940853,0.05377314,0.01311297,0.000658569,0.0001392077,0.00001081884,0.000001770559,0.01749981],"genre_scores_gemma":[0.9833665,0.00003898446,0.01599383,0.00004016283,0.0001245042,0.000002281748,0.00001102433,0.000003259372,0.0004194517],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7539024,"threshold_uncertainty_score":0.998477,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1471626567743256,"score_gpt":0.4162050942283174,"score_spread":0.2690424374539918,"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."}}