{"id":"W2743477489","doi":"10.11606/t.45.2016.tde-02052016-110000","title":"Estimação de modelos geoestatísticos com dados funcionais usando ondaletas","year":2016,"lang":"pt","type":"dissertation","venue":"","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Estimator; Pointwise; Context (archaeology); Kriging; Metropolitan area; Functional data analysis; Mean squared error; Geography; Computer science; Mathematics; Statistics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0004472836,0.0007550438,0.00061732,0.0001430741,0.0006149372,0.0001869595,0.0006704086,0.0004684308,0.01675558],"category_scores_gemma":[0.0002964823,0.0006380054,0.0002179262,0.000233291,0.0002682459,0.0002733037,0.0002221288,0.0004583933,0.004870091],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005917709,"about_ca_system_score_gemma":0.0002693268,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003492073,"about_ca_topic_score_gemma":0.000184167,"domain_scores_codex":[0.9959028,0.0001244468,0.000744271,0.00110142,0.0009790155,0.001148076],"domain_scores_gemma":[0.9977726,0.0004782641,0.0004084391,0.0006788237,0.00007918098,0.0005826675],"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":[0.0003469961,0.0008390269,0.01839717,0.0005618903,0.0003409956,0.0002724209,0.004368009,0.006180692,0.01408846,0.01327597,0.01243587,0.9288925],"study_design_scores_gemma":[0.002969628,0.0004090567,0.04421796,0.001040145,0.0006598122,0.00006379,0.001653166,0.9198864,0.002482937,0.01263012,0.0110983,0.002888703],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03697106,0.0002754501,0.9087089,0.0006620525,0.001409151,0.00120921,0.001071392,0.0001798217,0.04951298],"genre_scores_gemma":[0.916985,0.0004539846,0.006865134,0.000651509,0.00006268908,0.0001369691,0.001060562,0.0001163564,0.07366776],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9260038,"threshold_uncertainty_score":0.9996071,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01837608936771131,"score_gpt":0.2645874236581066,"score_spread":0.2462113342903953,"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."}}