{"id":"W2015813728","doi":"10.1007/s13253-012-0103-0","title":"Selection of Spatial-Temporal Lattice Models: Assessing the Impact of Climate Conditions on a Mountain Pine Beetle Outbreak","year":2012,"lang":"en","type":"article","venue":"Journal of Agricultural Biological and Environmental Statistics","topic":"Forest Insect Ecology and Management","field":"Environmental Science","cited_by":15,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Genome British Columbia; U.S. Department of Agriculture","keywords":"Bark beetle; Mountain pine beetle; Lasso (programming language); Selection (genetic algorithm); Model selection; Statistics; Econometrics; Ecology; Computer science; Mathematics; Biology; Machine learning; Bark (sound)","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002413876,0.0001102502,0.0001829669,0.000014793,0.0001203024,0.000008486675,0.0000789669,0.00005989336,0.0006880493],"category_scores_gemma":[0.00002058008,0.00004828009,0.00007038435,0.00005427845,0.0002835954,0.0001843921,0.0000875553,0.0001334485,0.000008827342],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001168567,"about_ca_system_score_gemma":0.000002127199,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001592622,"about_ca_topic_score_gemma":0.00001686317,"domain_scores_codex":[0.9991839,0.00009445561,0.0003239732,0.00007498864,0.0001447107,0.0001779621],"domain_scores_gemma":[0.9993765,0.0001246098,0.0003821105,0.00003922407,0.000005362093,0.00007215523],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001320747,0.001119365,0.9055837,0.00001338751,0.0001410731,0.00000414862,0.0003166141,0.01664719,0.07060735,0.0009578959,0.0008995371,0.003577638],"study_design_scores_gemma":[0.0002153548,0.001019088,0.9964477,0.000008929239,0.00004038603,0.0000586177,0.0003383117,0.000660687,0.0003307241,0.0007768077,0.00003281241,0.0000705481],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9984798,0.00003541316,0.0008289975,0.0000309794,0.00004693236,0.00009915647,0.0001565298,0.000001928912,0.0003202184],"genre_scores_gemma":[0.9983606,0.000315879,0.001189205,0.00002974298,0.00003717086,0.000001869881,0.00004666271,0.000002413982,0.0000164751],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.090864,"threshold_uncertainty_score":0.7533658,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01786767056644699,"score_gpt":0.2595196768304588,"score_spread":0.2416520062640118,"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."}}