{"id":"W1976915567","doi":"10.1142/s1793536913500015","title":"EOF-MSE ADAPTIVE METHOD TO ASSESS AN ACID DEPOSITION MONITORING NETWORK OVER ALBERTA, CANADA","year":2013,"lang":"en","type":"article","venue":"Advances in Adaptive Data Analysis","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Environment and Protected Areas","funders":"National Science Foundation","keywords":"Mean squared error; Statistics; Sampling (signal processing); Mathematics; Environmental science; Geography; Computer science; Telecommunications","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001295681,0.0005624764,0.0003486732,0.002336915,0.0005270857,0.0006618324,0.0008714126,0.0003547154,0.0008936658],"category_scores_gemma":[0.00441898,0.0001781508,0.0003080675,0.00254159,0.0002705679,0.0003109115,0.0004832547,0.0003896992,0.0001371272],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002405447,"about_ca_system_score_gemma":0.003989983,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6673615,"about_ca_topic_score_gemma":0.6884379,"domain_scores_codex":[0.99936,0.00009403726,0.00003688225,0.0001415158,0.0002867248,0.00008079528],"domain_scores_gemma":[0.9987716,0.0002441432,0.0001172116,0.00006283027,0.0007595645,0.00004466829],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0002588528,0.0001204884,0.2990974,0.0001309409,0.0002373462,0.0003327493,0.0003260738,0.3674855,0.009388544,0.002627309,0.005203737,0.3147911],"study_design_scores_gemma":[0.00001848378,0.00002142189,0.09722117,0.00001473822,0.00002695911,0.00005485412,0.0001911327,0.8972458,0.001630348,0.0008100768,0.002741107,0.00002398388],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6436406,0.0004612901,0.3420046,0.0002664392,0.00004501381,0.0002719774,0.005145136,0.001931467,0.006233448],"genre_scores_gemma":[0.7613196,0.0001495901,0.230644,0.00007369045,0.0000180752,0.0001391973,0.005056828,0.0001171477,0.002481956],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3326385,"threshold_uncertainty_score":0.6691949,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01973329836831457,"score_gpt":0.2866966226174634,"score_spread":0.2669633242491489,"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."}}