{"id":"W4200093916","doi":"10.1002/essoar.10508865.1","title":"Greater than averages: how metrics of extreme weather are trending differently than averages would suggest","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Climate variability and models","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Oceanic and Atmospheric Administration","keywords":"State (computer science); World Wide Web; Computer science; History; Programming language","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008963812,0.000926166,0.0008729072,0.004301132,0.001624726,0.008579529,0.001139289,0.001284735,0.005385942],"category_scores_gemma":[0.05900953,0.000418759,0.001200741,0.005829533,0.004796983,0.01764512,0.003489848,0.003048877,0.001286831],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00151412,"about_ca_system_score_gemma":0.001148335,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007575212,"about_ca_topic_score_gemma":0.006909768,"domain_scores_codex":[0.9942513,0.002262856,0.0004488864,0.001903689,0.0007838101,0.0003495397],"domain_scores_gemma":[0.9732991,0.01229716,0.005137193,0.004413264,0.003434939,0.001418368],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003721344,0.00006971396,0.4637247,0.0008199227,0.001014742,0.0003312427,0.02073571,0.004699336,0.001939836,0.2436302,0.03686499,0.2257976],"study_design_scores_gemma":[0.00002335017,0.0002844221,0.3616174,0.0007001746,0.0002465201,0.0006508764,0.01608124,0.009856221,0.0007443184,0.4940603,0.1154167,0.0003185431],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5257429,0.02656769,0.249099,0.07368289,0.007465905,0.0002771666,0.01258475,0.004427633,0.1001521],"genre_scores_gemma":[0.9538371,0.002771236,0.03274431,0.003385484,0.001658104,0.0001594343,0.002024139,0.0007417032,0.00267856],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008963812,"threshold_uncertainty_score":0.04740572,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06807442028023003,"score_gpt":0.246666935529487,"score_spread":0.178592515249257,"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."}}