{"id":"W7106714045","doi":"10.71781/32597","title":"Correction, guidée par les données, de distributions a priori biaisées en haute dimension pour l’astrophysique","year":2025,"lang":"en","type":"dissertation","venue":"Open MIND","topic":"Gaussian Processes and Bayesian Inference","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Institut Périmètre de physique théorique; Université de Montréal; Flatiron Health; McGill University","keywords":"Distribution (mathematics); A priori and a posteriori; Maximum likelihood; ESPACE","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005952799,0.002576507,0.002246261,0.002941509,0.001675891,0.007043576,0.003317021,0.002622548,0.01973182],"category_scores_gemma":[0.03699057,0.001844215,0.002928553,0.002641519,0.002078421,0.006047662,0.003781063,0.00604717,0.01237759],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002028866,"about_ca_system_score_gemma":0.00603112,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02133285,"about_ca_topic_score_gemma":0.02668333,"domain_scores_codex":[0.9948533,0.001337452,0.0003440851,0.001585227,0.001658738,0.0002213122],"domain_scores_gemma":[0.9877962,0.00572274,0.0006697816,0.002747726,0.00285923,0.0002044295],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0004663682,0.0001021446,0.006425851,0.001501362,0.0006232828,0.0003897217,0.001211267,0.09977563,0.02377375,0.07708735,0.03386978,0.7547735],"study_design_scores_gemma":[0.0001144651,0.0001659832,0.006203619,0.0008974292,0.000265891,0.001048857,0.001016353,0.6134548,0.02243649,0.1913553,0.1627858,0.0002550311],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002741214,0.001069177,0.988675,0.0007411728,0.0002377933,0.00006683344,0.000844392,0.002721344,0.002903101],"genre_scores_gemma":[0.08889863,0.003165066,0.8840768,0.00101088,0.000360516,0.0004370589,0.003834857,0.002127105,0.01608904],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02133285,"threshold_uncertainty_score":0.06600952,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02046299135171401,"score_gpt":0.2871335389951319,"score_spread":0.2666705476434179,"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."}}