{"id":"W6941868744","doi":"10.1371/journal.pone.0186525.t001","title":"Candidate model set with varying random effects structures and global fixed effects structure&lt;sup&gt;*&lt;/sup&gt; for three seasons, describing selection of landscape variables by wolves in northern Ontario, Canada, 2010–2014.","year":2017,"lang":"en","type":"dataset","venue":"Figshare","topic":"Mycorrhizal Fungi and Plant Interactions","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Selection (genetic algorithm); Set (abstract data type); Random variable; Random effects model; Data set; Model selection","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00171188,0.001749698,0.001695834,0.001799277,0.001558261,0.001827718,0.004520404,0.002033865,0.0733509],"category_scores_gemma":[0.01245413,0.001073689,0.002303153,0.00340522,0.0005504198,0.0009435666,0.001497864,0.00162747,0.02798061],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006348453,"about_ca_system_score_gemma":0.01661244,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6955627,"about_ca_topic_score_gemma":0.8706826,"domain_scores_codex":[0.9991641,0.0001717978,0.00008474199,0.0002727242,0.0001791441,0.0001275739],"domain_scores_gemma":[0.9947778,0.002056146,0.0002952217,0.0007525769,0.001701703,0.0004166009],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001244972,0.00003065828,0.005443729,0.001003272,0.0001903949,0.00004441108,0.00005421718,0.00160476,0.00008940743,0.0006418019,0.9880414,0.002731413],"study_design_scores_gemma":[0.00168314,0.00003825834,0.03220598,0.001198364,0.000410077,0.00009432599,0.0002848683,0.003253732,0.0002749668,0.002225598,0.9582312,0.00009939644],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002897275,0.00008345297,0.0001486109,0.00008513415,0.00001669672,0.00001528278,0.9988005,0.0001537741,0.0004067283],"genre_scores_gemma":[0.001701181,0.00006598458,0.0006070677,0.00006428533,0.000006658787,0.0001677416,0.9963235,0.00009739909,0.0009662919],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3044373,"threshold_uncertainty_score":0.6124603,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0117617283489416,"score_gpt":0.20248607703184,"score_spread":0.1907243486828984,"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."}}