{"id":"W2195586074","doi":"10.1139/cjfas-2015-0086","title":"Recent advances in statistical methodology applied to the Hjort liver index time series (1859–2012) and associated influential factors","year":2015,"lang":"en","type":"article","venue":"Canadian Journal of Fisheries and Aquatic Sciences","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Norges Forskningsråd; Havforskningsinstituttet","keywords":"Series (stratigraphy); Statistics; Econometrics; Index (typography); Arctic; Computer science; Ecology; Environmental science; Biology; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01460858,0.001151606,0.001001712,0.00586369,0.0006259388,0.002231272,0.001344126,0.0007855094,0.002479591],"category_scores_gemma":[0.04665136,0.0003781933,0.00146966,0.009572297,0.001963286,0.001803233,0.001307607,0.00274292,0.0005582487],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001382173,"about_ca_system_score_gemma":0.001935161,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01115516,"about_ca_topic_score_gemma":0.008443802,"domain_scores_codex":[0.9945465,0.002853358,0.0004887023,0.0009399448,0.001059096,0.0001123898],"domain_scores_gemma":[0.970033,0.02272895,0.002617532,0.001945097,0.0024174,0.0002580274],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007526926,0.00007200527,0.04815939,0.001861841,0.001069025,0.0004266698,0.0008509241,0.05009183,0.001682508,0.3165276,0.01099409,0.5681888],"study_design_scores_gemma":[0.00003137492,0.0001873415,0.1085098,0.001152662,0.0005186566,0.0008649488,0.0006607487,0.288938,0.002526469,0.453198,0.1430975,0.000314374],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01290304,0.03510234,0.9398909,0.003251524,0.001127434,0.00008623606,0.0009964035,0.0002565391,0.006385555],"genre_scores_gemma":[0.3686096,0.09137498,0.516564,0.001464304,0.009438362,0.0006578844,0.004543348,0.0005159999,0.006831512],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01460858,"threshold_uncertainty_score":0.07725847,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05027205723385931,"score_gpt":0.2817679167289853,"score_spread":0.231495859495126,"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."}}