{"id":"W7063174487","doi":"","title":"'Winterpeg' struggling with warmer weather","year":2024,"lang":"en","type":"other","venue":"Bulletin of Miscellaneous Information (Royal Gardens Kew)","topic":"Scientific Measurement and Uncertainty Evaluation","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Climate change; Cold weather; Work (physics); Weather forecasting; Government (linguistics)","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":[0.0006719294,0.0004115434,0.0003184112,0.0004122635,0.003637786,0.006263257,0.0005710897,0.001175108,0.08009147],"category_scores_gemma":[0.003258382,0.0002595512,0.0001621774,0.001231917,0.000887687,0.002031682,0.002242496,0.0018244,0.008750999],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005092121,"about_ca_system_score_gemma":0.01056601,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6235586,"about_ca_topic_score_gemma":0.8548402,"domain_scores_codex":[0.999405,0.00006808306,0.00001219326,0.00008833741,0.0002888175,0.0001375892],"domain_scores_gemma":[0.9989429,0.0001491814,0.00006139922,0.00006480499,0.000292707,0.0004890072],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005579492,0.00001288106,0.001844209,0.0002103575,0.000008591622,0.0003014529,0.0009332114,0.0001364464,0.0005183432,0.01006838,0.8965271,0.08938333],"study_design_scores_gemma":[0.000002180503,0.000003601707,0.003230029,0.00006220257,0.000002746192,0.00003955284,0.0007386485,0.0000338517,0.0001023149,0.000459576,0.9953197,0.000005657738],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.01961697,0.01689484,0.001969789,0.1299951,0.006226585,0.0001123612,0.005440033,0.0006238155,0.8191206],"genre_scores_gemma":[0.09220047,0.01376914,0.003056144,0.01484867,0.0004059067,0.00004724027,0.001974693,0.0007269963,0.8729708],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.3764414,"threshold_uncertainty_score":0.7573167,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03805241181465088,"score_gpt":0.2720150311472518,"score_spread":0.2339626193326009,"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."}}