{"id":"W2137101945","doi":"10.1002/cjs.5550350401","title":"Stationary state space models for longitudinal data","year":2007,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"State space; Kalman filter; State-space representation; Range (aeronautics); Applied mathematics; Computer science; Mathematics; Statistics; Econometrics; Statistical physics; Algorithm; Physics; Engineering","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001968702,0.0001425753,0.0003011785,0.0002034837,0.0001401489,0.00006574369,0.0004594816,0.000051544,0.000136723],"category_scores_gemma":[0.005253987,0.0001319048,0.00003386235,0.0001288514,0.0001379874,0.0002023546,0.00002472429,0.0002159594,0.000003323925],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001270669,"about_ca_system_score_gemma":0.001363267,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006937682,"about_ca_topic_score_gemma":0.01277917,"domain_scores_codex":[0.9983781,0.0000472818,0.0006894269,0.0001720347,0.0002646658,0.000448474],"domain_scores_gemma":[0.9940343,0.003642889,0.0003886379,0.0003418007,0.0008353175,0.0007569763],"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":[0.00005836439,0.00002353142,0.0005879518,0.00009959473,0.00006902863,0.0003272243,0.0003338644,0.0001209203,0.00001053435,0.8828963,0.07839089,0.03708182],"study_design_scores_gemma":[0.0004101591,0.0002039062,0.00197228,0.00006103769,0.00008203482,0.00009389433,0.0001678151,0.01395405,0.00003035876,0.9768295,0.00602521,0.0001697832],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001400184,0.0001310298,0.9890515,0.0001862654,0.0004226584,0.0001556601,0.007979224,0.000004986097,0.0006684464],"genre_scores_gemma":[0.0530379,0.00001858344,0.9463785,0.00008856149,0.0001593146,9.996179e-7,0.00005401466,0.00002892932,0.0002331637],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.09393319,"threshold_uncertainty_score":0.7131076,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3834474582654898,"score_gpt":0.3984552869877093,"score_spread":0.01500782872221945,"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."}}