{"id":"W6981030944","doi":"","title":"Determinants of Canadian outward FDI: variable selection using bayesian statistical techniques","year":2018,"lang":"ca","type":"dissertation","venue":"Repositori UJI (Universitat Jaume I)","topic":"Endometriosis Research and Treatment","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Variable (mathematics); Bayesian probability; Selection (genetic algorithm); Feature selection; Statistical analysis; Statistical model; Model selection; Bayes' theorem","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000438047,0.0006094868,0.001191381,0.004362497,0.0007367049,0.0001015311,0.0003274184,0.0008483226,0.0006458317],"category_scores_gemma":[0.0008804476,0.0006633024,0.0002665709,0.003039103,0.0001850343,0.0003766221,0.00006131236,0.0006090531,0.00005662309],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003201151,"about_ca_system_score_gemma":0.003748305,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.3551035,"about_ca_topic_score_gemma":0.07806783,"domain_scores_codex":[0.9958701,0.00027807,0.0007197481,0.0008990958,0.001110295,0.001122764],"domain_scores_gemma":[0.9955269,0.0005106469,0.000571923,0.0005576643,0.001586441,0.001246465],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.01271777,0.004903758,0.5329897,0.01482172,0.01359953,0.02153945,0.01351603,0.0000333547,0.2317918,0.008194192,0.03625134,0.1096414],"study_design_scores_gemma":[0.01559426,0.0302692,0.06920111,0.01930143,0.02035941,0.003123499,0.02957225,0.02224106,0.6697149,0.00113205,0.1134304,0.006060416],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8959627,0.001885415,0.0159367,0.0001676224,0.006926557,0.0065922,0.001534005,0.0003623727,0.07063243],"genre_scores_gemma":[0.9095548,0.0005466025,0.07894245,0.00001637188,0.001069544,0.00002246773,0.001046016,0.0001460735,0.008655615],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4637885,"threshold_uncertainty_score":0.9995818,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01857077768266897,"score_gpt":0.3103702301706315,"score_spread":0.2917994524879626,"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."}}