{"id":"W4386648239","doi":"10.20944/preprints202309.0764.v1","title":"Some Matrix-variate Models Applicable in Different Areas","year":2023,"lang":"en","type":"preprint","venue":"Preprints.org","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"TRACE (psycholinguistics); Exponent; Constant (computer programming); Wishart distribution; Mathematics; Type (biology); Matrix (chemical analysis); Exponential function; Gaussian; Domain (mathematical analysis); Exponential family; Exponential type; Random variate; Applied mathematics; Mathematical analysis; Statistics; Computer science; Random variable; Physics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001898382,0.001362576,0.0009345921,0.001821002,0.0009088763,0.003013356,0.002584943,0.002169859,0.01088545],"category_scores_gemma":[0.007558654,0.0005461102,0.001756019,0.003711583,0.001745939,0.003999638,0.001497554,0.003360342,0.004384948],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001582802,"about_ca_system_score_gemma":0.001008532,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005263908,"about_ca_topic_score_gemma":0.00389155,"domain_scores_codex":[0.9980819,0.0006990646,0.00008336398,0.0004344024,0.0004925726,0.0002086929],"domain_scores_gemma":[0.996568,0.001786574,0.0004232576,0.0003902561,0.0007302838,0.0001016851],"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":[0.00003284699,0.00004310776,0.001254577,0.0001623268,0.00004124736,0.000298221,0.0002526818,0.03463727,0.0009010828,0.9293048,0.006579769,0.02649203],"study_design_scores_gemma":[0.00001087948,0.00006138921,0.001046392,0.00009737461,0.00004255581,0.0006869652,0.0001473599,0.3299596,0.001208489,0.6286307,0.03803327,0.00007498044],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0108913,0.004040624,0.9525341,0.00171385,0.0004134065,0.00007679503,0.0007277936,0.0004122545,0.02918988],"genre_scores_gemma":[0.5491908,0.01675356,0.3161904,0.002395046,0.001815083,0.000730507,0.002305049,0.0008302783,0.1097894],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01088545,"threshold_uncertainty_score":0.03641546,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4358174872920702,"score_gpt":0.4852245706749035,"score_spread":0.04940708338283334,"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."}}