{"id":"W4384834058","doi":"10.1093/jrsssc/qlad064","title":"A Tweedie Markov process and its application in fisheries stock assessment","year":2023,"lang":"en","type":"article","venue":"Journal of the Royal Statistical Society Series C (Applied Statistics)","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Autoregressive model; Markov chain; Applied mathematics; Econometrics; Autocorrelation; Computer science; Mathematics; Statistics","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":[0.005889033,0.0006392329,0.0009696725,0.00240467,0.0008977652,0.001767382,0.001968657,0.001946351,0.003853361],"category_scores_gemma":[0.02076789,0.0006622268,0.001146698,0.002037694,0.00174467,0.00262973,0.00188357,0.002688255,0.0005910536],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001333818,"about_ca_system_score_gemma":0.001054681,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008809227,"about_ca_topic_score_gemma":0.005050333,"domain_scores_codex":[0.9983381,0.0007162908,0.00008754269,0.0004139302,0.0003424411,0.0001016511],"domain_scores_gemma":[0.9871072,0.01013186,0.0009634286,0.0006177559,0.0009160137,0.0002638458],"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":[0.0001427479,0.00009425533,0.006444295,0.0001256556,0.00008459104,0.0003775712,0.0002658812,0.7177931,0.00225191,0.196492,0.001140004,0.0747879],"study_design_scores_gemma":[0.000005787248,0.0000173023,0.0003235991,0.00001419075,0.000009195316,0.00004637498,0.00001340997,0.9713697,0.0003372288,0.02721874,0.0006238865,0.00002053791],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01448537,0.0002186312,0.9843523,0.0002250537,0.00003416714,0.00003867076,0.00006700398,0.00010193,0.000476866],"genre_scores_gemma":[0.6020621,0.0009897734,0.3906361,0.0002039017,0.0001335721,0.0003146332,0.000454421,0.0001150049,0.005090558],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008809227,"threshold_uncertainty_score":0.03114456,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01428560951854732,"score_gpt":0.2886606889203223,"score_spread":0.274375079401775,"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."}}