{"id":"W7106709396","doi":"10.34989/drb0-zr06","title":"Supplemental material for \"Calculating Effective Degrees of Freedom for Forecast Combinations and Ensemble Models\"","year":2025,"lang":"en","type":"dataset","venue":"Bank of Canada Research","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bank of Canada","funders":"","keywords":"Degrees of freedom (physics and chemistry); Key (lock); Ensemble forecasting; Stability (learning theory)","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":[0.00188907,0.00208236,0.001361175,0.00243704,0.0008781453,0.002040564,0.002947184,0.002040559,0.2777839],"category_scores_gemma":[0.01110255,0.0009541956,0.001404722,0.004367723,0.0003390449,0.001325272,0.001679463,0.002143902,0.1885887],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002154754,"about_ca_system_score_gemma":0.002769892,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05063775,"about_ca_topic_score_gemma":0.1313071,"domain_scores_codex":[0.9988629,0.0002364296,0.0001201336,0.000232285,0.000354031,0.000194279],"domain_scores_gemma":[0.9943504,0.002370756,0.0003129156,0.001102963,0.001620193,0.0002428273],"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":[0.000016466,0.00001266625,0.0002425506,0.0001499729,0.00001352196,0.000004215698,0.000004467403,0.0002520852,0.00002080594,0.0002954401,0.9972814,0.001706414],"study_design_scores_gemma":[0.0004918707,0.00002711805,0.005491426,0.0004389294,0.00004737109,0.00007215849,0.00007862307,0.002357559,0.0004373926,0.005918551,0.9845906,0.00004831766],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00008488238,0.00003693519,0.0002363368,0.00004503433,0.00003922079,0.00001032898,0.9984303,0.000423065,0.0006938011],"genre_scores_gemma":[0.0005367604,0.00004612501,0.001080129,0.00006444953,0.00001681845,0.00009953875,0.9967614,0.000180651,0.001214104],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2777839,"threshold_uncertainty_score":0.9292798,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04984682202529575,"score_gpt":0.3567672840015437,"score_spread":0.3069204619762479,"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."}}