{"id":"W7103432225","doi":"","title":"Modeling Size-of-Loss Distributions for Exact Data\\nin WinBUGS","year":2002,"lang":"","type":"article","venue":"Insecta mundi","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Inverse; Weibull distribution; Bayesian probability; Inverse problem; Statistical model; Statistical analysis; Software; Estimation theory","routes":{"ca_aff":true,"ca_fund":true,"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":[0.01077556,0.0006697094,0.001184409,0.001512074,0.0004582303,0.001727398,0.001780105,0.0009100375,0.002596944],"category_scores_gemma":[0.03594731,0.0006174987,0.0009681793,0.001199229,0.001384021,0.003077163,0.001882965,0.001724972,0.000460921],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001441022,"about_ca_system_score_gemma":0.001353818,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004140536,"about_ca_topic_score_gemma":0.005173351,"domain_scores_codex":[0.9968369,0.001624261,0.0001771363,0.000448701,0.0007178141,0.000195093],"domain_scores_gemma":[0.9839931,0.01117398,0.001454053,0.002241536,0.0009541212,0.0001831764],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002339497,0.00008731521,0.02065306,0.000126839,0.000122467,0.0002474249,0.0007145593,0.6525342,0.003097093,0.2162527,0.001826145,0.1041043],"study_design_scores_gemma":[0.00001454897,0.00004678668,0.002709153,0.00002260338,0.00001204813,0.000107636,0.0000877652,0.8929299,0.001152529,0.1009866,0.001905658,0.00002492141],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05798925,0.0000627778,0.9401166,0.0001228069,0.00001951785,0.0000564167,0.0001849308,0.0005574629,0.0008901646],"genre_scores_gemma":[0.6805537,0.0002044945,0.315253,0.0001325667,0.00003298005,0.0003691176,0.0008719143,0.0003562871,0.00222588],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01077556,"threshold_uncertainty_score":0.05698735,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2355765968149291,"score_gpt":0.3900776103478357,"score_spread":0.1545010135329065,"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."}}