{"id":"W7124199036","doi":"10.65109/jsvv3990","title":"Eliciting forecasts from self-interested experts: scoring rules for decision makers","year":2012,"lang":"","type":"article","venue":"","topic":"Forecasting Techniques and Applications","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Expert system; Scoring rule; Incentive; Decision rule; Compensation (psychology); Principal (computer security); Decision tree; Decision maker; Function (biology)","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":[0.02965257,0.001249088,0.001894478,0.001429913,0.000942181,0.003398821,0.002380604,0.003134344,0.002795134],"category_scores_gemma":[0.1004685,0.0007338169,0.0009234555,0.001390845,0.002379795,0.005507832,0.002159538,0.003094478,0.0007286317],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00141272,"about_ca_system_score_gemma":0.001501262,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008161896,"about_ca_topic_score_gemma":0.0008912919,"domain_scores_codex":[0.9816629,0.01064711,0.001472611,0.001830391,0.003752954,0.0006339726],"domain_scores_gemma":[0.9125858,0.0657044,0.00783111,0.007170525,0.005454117,0.001253999],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003599418,0.0002409636,0.005851304,0.0003112401,0.0002171588,0.0004488312,0.0009518921,0.3805576,0.004215848,0.4411063,0.003182154,0.1625568],"study_design_scores_gemma":[0.00005557733,0.00008122013,0.0006429623,0.0000718372,0.00002810833,0.0001126887,0.00006685263,0.6949043,0.001936448,0.300771,0.001288449,0.00004057478],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03267635,0.0002148838,0.9628274,0.0005012115,0.00003364245,0.0001338034,0.00005788785,0.0000793659,0.003475433],"genre_scores_gemma":[0.6810321,0.0005168902,0.3142993,0.0002460924,0.0001482446,0.0004114801,0.0001673913,0.00004268468,0.003135797],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02965257,"threshold_uncertainty_score":0.1568196,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1696737677009666,"score_gpt":0.4163339975800721,"score_spread":0.2466602298791055,"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."}}