{"id":"W4404041059","doi":"10.1097/01.pcc.0001085680.58340.0d","title":"PP338 Topic: AS09–Global Health/Resource Limited Setting/Health Inequalities/Impact of Global Warming/Other: IMPACT OF IN-PERSON VS VIRTUAL ATTENDANCE ON THE CARBON FOOTPRINT OF CONSENSUS CONFERENCES: COMPARISON OF PALICC AND PALICC-2","year":2024,"lang":"en","type":"article","venue":"Pediatric Critical Care Medicine","topic":"Global Public Health Policies and Epidemiology","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre Hospitalier Universitaire Sainte-Justine; Université de Montréal; École de Technologie Supérieure","funders":"","keywords":"Medicine; Carbon footprint; Attendance; Inequality; Global warming; Global health; Footprint; Resource (disambiguation); Environmental resource management; Climate change; Greenhouse gas; Economic growth; Public health; Environmental science; Nursing; Oceanography; Geography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.002202112,0.0005721884,0.0004999537,0.001546922,0.0007096538,0.002516629,0.000908089,0.001089352,0.2142875],"category_scores_gemma":[0.004832831,0.0001433916,0.0006581731,0.00321899,0.0004493514,0.001772809,0.00215205,0.0009531662,0.0279466],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001197283,"about_ca_system_score_gemma":0.002463984,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00532277,"about_ca_topic_score_gemma":0.007727742,"domain_scores_codex":[0.9990066,0.0003124214,0.00008087484,0.0001340848,0.0003200084,0.0001460308],"domain_scores_gemma":[0.9962286,0.001026787,0.0003969242,0.0001892948,0.001423965,0.0007345682],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0002870144,0.00008233356,0.008767894,0.003631191,0.00003893326,0.00007335382,0.0004080803,0.0001658839,0.0005869473,0.002583171,0.8783928,0.1049825],"study_design_scores_gemma":[0.00004361629,0.0001848614,0.05451339,0.001660812,0.00003047203,0.0001662516,0.001536594,0.0001442041,0.0003059586,0.001056832,0.9403384,0.00001863054],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.0726152,0.05014493,0.002693587,0.05251214,0.03959411,0.002069615,0.1161762,0.0009702712,0.663224],"genre_scores_gemma":[0.3809522,0.08000928,0.01284021,0.02012857,0.02787592,0.004774787,0.1459582,0.001924601,0.3255363],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.2142875,"threshold_uncertainty_score":0.7168632,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07346879793166554,"score_gpt":0.4197045048714436,"score_spread":0.346235706939778,"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."}}