{"id":"W4411430209","doi":"10.5194/essd-18-4019-2026","title":"A daily gridded high-resolution meteorological data set for historical impact studies in Switzerland since 1763","year":2025,"lang":"en","type":"preprint","venue":"Earth system science data","topic":"Tree-ring climate responses","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Horizon 2020 Framework Programme; European Commission; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation","keywords":"Relative humidity; Sunshine duration; Climatology; Environmental science; Precipitation; Wind speed; Mean radiant temperature; Mean squared error; Meteorology; Angstrom; Atmospheric sciences; Climate change; Geography; Mathematics; Statistics; Geology","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":[0.0003660139,0.0006296497,0.0002864152,0.002226847,0.0003437434,0.0004826114,0.0003076639,0.0003756982,0.003587352],"category_scores_gemma":[0.0008082284,0.0001424884,0.0004274537,0.003123604,0.0001985318,0.0002939815,0.0003644374,0.0003201441,0.001332481],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006612814,"about_ca_system_score_gemma":0.0007518625,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07878789,"about_ca_topic_score_gemma":0.08982085,"domain_scores_codex":[0.9997092,0.00004666438,0.00002907669,0.00007970291,0.00009276081,0.00004258678],"domain_scores_gemma":[0.9994113,0.00007314219,0.0001309292,0.00009648032,0.0002135702,0.00007445424],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008612143,0.000395316,0.644867,0.0008082394,0.0006237114,0.002182869,0.001079784,0.1168287,0.01334237,0.001698454,0.1278932,0.0894191],"study_design_scores_gemma":[0.00004570237,0.0000544431,0.9600186,0.0000516607,0.00003618439,0.0001118147,0.0002261559,0.0155913,0.001132504,0.0001302177,0.02255455,0.00004692573],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"dataset","genre_scores_codex":[0.6600235,0.0005158267,0.00301894,0.0001552983,0.00008284533,0.0001405119,0.3310316,0.0006184386,0.004412952],"genre_scores_gemma":[0.6195117,0.0002359027,0.003595751,0.00002693869,0.00004784567,0.0003215825,0.3748484,0.00007566073,0.001336224],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.07878789,"threshold_uncertainty_score":0.1566586,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2022535242547594,"score_gpt":0.3704766355546769,"score_spread":0.1682231112999175,"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."}}