{"id":"W2090846039","doi":"10.1016/j.ecolmodel.2011.11.001","title":"Performance of a Bayesian state-space model of semelparous species for stock-recruitment data subject to measurement error","year":2011,"lang":"en","type":"article","venue":"Ecological Modelling","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":41,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Stock assessment; Bayesian probability; Stock (firearms); Econometrics; Statistics; Observational error; Fish stock; Statistical model; Computer science; Ecology; Mathematics; Fishery; Biology; Fish <Actinopterygii>; Geography","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":[0.01891111,0.0009186176,0.001552756,0.0009151964,0.0009136743,0.002089105,0.001932757,0.002985566,0.001905473],"category_scores_gemma":[0.04995848,0.001199063,0.0009094221,0.0006597007,0.001275722,0.003018952,0.00166389,0.001803273,0.0004570174],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002180879,"about_ca_system_score_gemma":0.003449328,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03590356,"about_ca_topic_score_gemma":0.01871241,"domain_scores_codex":[0.997825,0.001367309,0.0001461308,0.0003184026,0.0002007746,0.0001422831],"domain_scores_gemma":[0.9522676,0.04291994,0.001279616,0.0009393407,0.001963847,0.0006296426],"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":[0.0003149048,0.00003049466,0.002298855,0.00002295638,0.00005344874,0.00001631821,0.00004941795,0.9861698,0.0003427945,0.002279863,0.0001546563,0.008266453],"study_design_scores_gemma":[0.00001067713,0.00001225473,0.0002528584,0.000002541341,0.000006404647,0.000003039558,0.000002806685,0.9987932,0.00009824571,0.0007970017,0.0000156701,0.000005292243],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4874632,0.0003476214,0.5082346,0.001163327,0.0000591467,0.00008612887,0.0003119049,0.0007449068,0.001589091],"genre_scores_gemma":[0.9518281,0.0001305947,0.0453101,0.0001471366,0.00002901666,0.00008512916,0.0005808359,0.0001258151,0.001763253],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03590356,"threshold_uncertainty_score":0.1000127,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4372118830118839,"score_gpt":0.314475051646644,"score_spread":0.1227368313652399,"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."}}