{"id":"W2586179334","doi":"10.5194/gmd-10-571-2017","title":"Half a degree additional warming, prognosis and projected impacts (HAPPI): background and experimental design","year":2017,"lang":"en","type":"article","venue":"Geoscientific model development","topic":"Climate variability and models","field":"Environmental Science","cited_by":267,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria; Environment and Climate Change Canada","funders":"Biological and Environmental Research; Bundesministerium für Umwelt, Naturschutz, nukleare Sicherheit und Verbraucherschutz; Office of Science; Ministry of Education, Culture, Sports, Science and Technology; Norges Forskningsråd; Sight Research UK; National Energy Research Scientific Computing Center; Natural Environment Research Council; U.S. Department of Energy","keywords":"Greenhouse gas; Climatology; Environmental science; Climate change; Representative Concentration Pathways; Global warming; Climate model; Degree (music); Range (aeronautics); Atmospheric sciences; Meteorology; Geography; Ecology","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":[0.01791125,0.001558177,0.001013709,0.000646784,0.001563517,0.001272002,0.002348951,0.00166698,0.01080414],"category_scores_gemma":[0.0264284,0.0008262552,0.002220621,0.0009596559,0.0025099,0.001333033,0.00256419,0.003020853,0.001219078],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002136818,"about_ca_system_score_gemma":0.003041663,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002453132,"about_ca_topic_score_gemma":0.001591287,"domain_scores_codex":[0.9890556,0.006385743,0.0007621477,0.001847234,0.001387062,0.0005622137],"domain_scores_gemma":[0.9762295,0.01190563,0.003212359,0.004306864,0.003342849,0.001002863],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"randomized_trial","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.3264903,0.06781783,0.04328997,0.01117778,0.003574769,0.0004564537,0.002090157,0.1275039,0.05859211,0.09144057,0.01955488,0.2480113],"study_design_scores_gemma":[0.0783724,0.3983645,0.06478619,0.001280022,0.005611743,0.0002865061,0.001842856,0.1054484,0.06763837,0.1321325,0.1431875,0.00104897],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.5180937,0.002391353,0.1943332,0.001258989,0.002069841,0.2424544,0.01267209,0.0009797232,0.02574673],"genre_scores_gemma":[0.3118222,0.0008121522,0.1628097,0.001065244,0.0003411305,0.5144897,0.003647187,0.0001695514,0.004843084],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.01791125,"threshold_uncertainty_score":0.09472483,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1252115238429699,"score_gpt":0.2890104583523889,"score_spread":0.1637989345094191,"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."}}