{"id":"W2947034755","doi":"10.5220/0007708201580166","title":"Generalized Dirichlet Regression and other Compositional Models with Application to Market-share Data Mining of Information Technology Companies","year":2019,"lang":"en","type":"article","venue":"","topic":"Grey System Theory Applications","field":"Decision Sciences","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"","keywords":"Latent Dirichlet allocation; Computer science; Data modeling; Regression analysis; Regression; Topic model; Data mining; Econometrics; Data science; Artificial intelligence; Statistics; Machine learning; Mathematics; Database","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":[0.01274697,0.001085111,0.003044623,0.003642379,0.001442984,0.002512276,0.003349148,0.002108472,0.002948571],"category_scores_gemma":[0.04592209,0.0008086968,0.003639042,0.004276093,0.001791425,0.003527432,0.002355018,0.002464816,0.0005726937],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001465536,"about_ca_system_score_gemma":0.001448946,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01037828,"about_ca_topic_score_gemma":0.01323314,"domain_scores_codex":[0.9953706,0.003088834,0.0002106946,0.0006412058,0.0004352432,0.0002534167],"domain_scores_gemma":[0.9703288,0.02669235,0.0008409439,0.001197431,0.0006856499,0.0002547539],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005240829,0.00035303,0.01639289,0.0004239485,0.0007597973,0.0003929698,0.001140164,0.6840571,0.001424213,0.1763605,0.003046444,0.1151249],"study_design_scores_gemma":[0.00001785517,0.00001787602,0.0009135109,0.00001376835,0.00003337054,0.00002498868,0.00006692627,0.925285,0.0001927266,0.07298119,0.0004362447,0.00001660793],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1754956,0.001333659,0.8189334,0.001190289,0.0001068934,0.0001619703,0.0007219194,0.0004108694,0.001645391],"genre_scores_gemma":[0.843282,0.001028569,0.1464891,0.0002747241,0.000286869,0.0002950446,0.001895199,0.0001755038,0.006273032],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01274697,"threshold_uncertainty_score":0.06741327,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07290700291791297,"score_gpt":0.3502497025460311,"score_spread":0.2773426996281181,"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."}}