{"id":"W7036408285","doi":"","title":"Bon usage des inhibiteurs de la pompe à protons à l'officine","year":2023,"lang":"fr","type":"dissertation","venue":"HAL AMU","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Pharmaceutical technology; Iatrogenic disease","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":[0.0009034806,0.0004882064,0.0004143382,0.0003410731,0.0003801215,0.000655161,0.001127701,0.0005952962,0.00004340593],"category_scores_gemma":[0.0006387412,0.000469739,0.0001685593,0.001248498,0.0003047065,0.0004938122,0.0002734469,0.001021801,0.0001936723],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000219893,"about_ca_system_score_gemma":0.0004734585,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002206674,"about_ca_topic_score_gemma":0.0006698209,"domain_scores_codex":[0.9972237,0.0003509891,0.0004427055,0.0007779897,0.0004823253,0.0007222594],"domain_scores_gemma":[0.9983121,0.0003668864,0.0003020236,0.0005182914,0.0003031836,0.0001975424],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001561383,0.000683343,0.006943834,0.005383718,0.0001445813,0.003446585,0.06731918,0.00007652024,0.1386264,0.2091856,0.007939679,0.5600944],"study_design_scores_gemma":[0.001061539,0.0008455351,0.02789317,0.0132058,0.0002528893,0.0007782005,0.001612524,0.0210997,0.6955242,0.2230237,0.01178632,0.002916381],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.7350914,0.03041819,0.2002843,0.00315638,0.002836643,0.004312724,0.0000700361,0.007981231,0.01584909],"genre_scores_gemma":[0.3884453,0.0003429682,0.549011,0.0005426927,0.0006617037,0.0005743076,0.0003398102,0.0002166358,0.05986562],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.557178,"threshold_uncertainty_score":0.9997754,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02212091463634494,"score_gpt":0.3203811642730099,"score_spread":0.298260249636665,"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."}}