{"id":"W6917600294","doi":"10.57757/iugg23-4054","title":"Outreach of climate change attribution in Hungary using seasonal indicators","year":2023,"lang":"en","type":"article","venue":"Publication Database GFZ (GFZ German Research Centre for Geosciences)","topic":"Climate Change and Environmental Impact","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Climate change; Outreach; Forcing (mathematics); Global warming; Climate model; Attribution; Quarter (Canadian coin)","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.004135188,0.0001751986,0.0001986845,0.0007537362,0.0004313558,0.00009517428,0.0006760235,0.00008770575,0.001422198],"category_scores_gemma":[0.0003806656,0.0001679437,0.00007639155,0.00389612,0.000621798,0.001615699,0.001001292,0.0002286474,0.0004197212],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005619212,"about_ca_system_score_gemma":0.00004322431,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001672052,"about_ca_topic_score_gemma":0.0007602365,"domain_scores_codex":[0.9960821,0.000199387,0.0004145126,0.0006876502,0.001338334,0.001277966],"domain_scores_gemma":[0.9986528,0.0002296997,0.0001813644,0.0005457733,0.00004181925,0.0003485663],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007613302,0.0005719994,0.9260323,0.0001381237,0.000007459412,0.000007481862,0.001737559,0.00005580842,0.007690499,0.000559449,0.01549146,0.04763175],"study_design_scores_gemma":[0.0008405155,0.00009868632,0.8930002,0.00009899329,0.00001222178,0.00000547391,0.001110776,0.04479319,0.002636718,0.0002123219,0.05683585,0.0003549811],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9905636,0.00003768997,0.00008253125,0.00266593,0.0001110608,0.001154595,0.004830201,0.00005992253,0.0004944945],"genre_scores_gemma":[0.9904253,0.0007214393,0.0004953734,0.0001563185,0.0001047809,0.0002398829,0.007599123,0.00002839049,0.0002293225],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04727677,"threshold_uncertainty_score":0.9994906,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1358287348189259,"score_gpt":0.3875224887711933,"score_spread":0.2516937539522675,"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."}}