{"id":"W4388268080","doi":"10.1007/s40304-023-00362-6","title":"Automatic Structure Identification of Semiparametric Spatial Autoregressive Model Based on Smooth-Threshold Estimating Equation","year":2023,"lang":"en","type":"article","venue":"Communications in Mathematics and Statistics","topic":"Spatial and Panel Data Analysis","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Autoregressive model; Structural equation modeling; Semiparametric model; Identification (biology); Computer science; Econometrics; STAR model; Semiparametric regression; Applied mathematics; Mathematics; Pattern recognition (psychology); Artificial intelligence; Statistics; Autoregressive integrated moving average; Time series; Nonparametric 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":[0.00126988,0.0005360466,0.001154495,0.0008006613,0.0003473046,0.001023391,0.001227238,0.0008473034,0.001835995],"category_scores_gemma":[0.005767422,0.0006135461,0.001177195,0.0008092911,0.0004550928,0.001362063,0.001199261,0.001438342,0.0005362125],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000463128,"about_ca_system_score_gemma":0.00141043,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005214312,"about_ca_topic_score_gemma":0.004628791,"domain_scores_codex":[0.9994588,0.0002055002,0.00003387097,0.000159437,0.00008683579,0.00005550986],"domain_scores_gemma":[0.9979267,0.001415976,0.0001856705,0.0001618661,0.0002563952,0.00005337066],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001500081,0.00009848203,0.00515801,0.0001970795,0.0001758001,0.0002422238,0.0002939931,0.726337,0.009998054,0.1213111,0.002159703,0.1338786],"study_design_scores_gemma":[0.000002956161,0.00000591691,0.0002182953,0.000003277374,0.000007487547,0.00001138026,0.000004437905,0.9915224,0.0002303734,0.007849649,0.0001394804,0.000004293258],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01533996,0.00006526474,0.9839856,0.00005860882,0.000009321851,0.000009259104,0.00004324644,0.0001678144,0.0003208307],"genre_scores_gemma":[0.6974474,0.0004088088,0.2962655,0.00007367256,0.00005672964,0.0001578031,0.0008591262,0.0002327031,0.004498319],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005214312,"threshold_uncertainty_score":0.01036793,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08834069153125292,"score_gpt":0.3073641395665165,"score_spread":0.2190234480352636,"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."}}